{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function\n",
    "import argparse\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "from torchvision import datasets, transforms\n",
    "import numpy as  np\n",
    "import matplotlib.pyplot as plt\n",
    "class Net(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(1, 20, 5, 1) #Conv2d(1, 20, kernel_size=(5, 5), stride=(1, 1))\n",
    "        self.conv2 = nn.Conv2d(20, 50, 5, 1)\n",
    "        self.fc1 = nn.Linear(4*4*50, 500)\n",
    "        self.fc2 = nn.Linear(500, 10)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = F.relu(self.conv1(x))\n",
    "        x = F.max_pool2d(x, 2, 2)\n",
    "        x = F.relu(self.conv2(x))\n",
    "        x = F.max_pool2d(x, 2, 2)\n",
    "        x = x.view(-1, 4*4*50)\n",
    "        x = F.relu(self.fc1(x))\n",
    "        x = self.fc2(x)\n",
    "        return F.log_softmax(x, dim=1)\n",
    "    \n",
    "def train(args, model, device, train_loader, optimizer, epoch):\n",
    "    model.train()\n",
    "    for batch_idx, (data, target) in enumerate(train_loader):\n",
    "        data, target = data.to(device), target.to(device)\n",
    "        optimizer.zero_grad()\n",
    "        output = model(data)\n",
    "        loss = F.nll_loss(output, target)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        if batch_idx % args.log_interval == 0:\n",
    "            print('Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}'.format(\n",
    "                epoch, batch_idx * len(data), len(train_loader.dataset),\n",
    "                100. * batch_idx / len(train_loader), loss.item()))\n",
    "\n",
    "def test(args, model, device, test_loader):\n",
    "    model.eval()\n",
    "    test_loss = 0\n",
    "    correct = 0\n",
    "    with torch.no_grad():\n",
    "        for data, target in test_loader:\n",
    "            data, target = data.to(device), target.to(device)\n",
    "            output = model(data)\n",
    "            test_loss += F.nll_loss(output, target, reduction='sum').item() # sum up batch loss\n",
    "            pred = output.argmax(dim=1, keepdim=True) # get the index of the max log-probability\n",
    "            correct += pred.eq(target.view_as(pred)).sum().item()\n",
    "\n",
    "    test_loss /= len(test_loader.dataset)\n",
    "\n",
    "    print('\\nTest set: Average loss: {:.4f}, Accuracy: {}/{} ({:.0f}%)\\n'.format(\n",
    "        test_loss, correct, len(test_loader.dataset),\n",
    "        100. * correct / len(test_loader.dataset)))\n",
    "\n",
    "parser = argparse.ArgumentParser(description='PyTorch MNIST Example')\n",
    "parser.add_argument('--batch-size', type=int, default=64, metavar='N',\n",
    "                    help='input batch size for training (default: 64)')\n",
    "parser.add_argument('--test-batch-size', type=int, default=1000, metavar='N',\n",
    "                    help='input batch size for testing (default: 1000)')\n",
    "parser.add_argument('--epochs', type=int, default=10, metavar='N',\n",
    "                    help='number of epochs to train (default: 10)')\n",
    "parser.add_argument('--lr', type=float, default=0.01, metavar='LR',\n",
    "                    help='learning rate (default: 0.01)')\n",
    "parser.add_argument('--momentum', type=float, default=0.5, metavar='M',\n",
    "                    help='SGD momentum (default: 0.5)')\n",
    "parser.add_argument('--no-cuda', action='store_true', default=False,\n",
    "                    help='disables CUDA training')\n",
    "parser.add_argument('--seed', type=int, default=1, metavar='S',\n",
    "                    help='random seed (default: 1)')\n",
    "parser.add_argument('--log-interval', type=int, default=10, metavar='N',\n",
    "                    help='how many batches to wait before logging training status')\n",
    "\n",
    "parser.add_argument('--save-model', action='store_true', default=False,\n",
    "                    help='For Saving the current Model')\n",
    "class arg:\n",
    "    def __init__(self):\n",
    "        self.batch_size= 64\n",
    "        self.test_batch_size= 1000\n",
    "        self.epochs = 2\n",
    "        self.lr = 0.01\n",
    "        self.momentum = 0.5\n",
    "        self.no_cuda = True\n",
    "        self.seed = 42\n",
    "        self.log_interval = 10\n",
    "        self.save_model = True\n",
    "args= arg()\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 1 [0/60000 (0%)]\tLoss: 2.309220\n",
      "Train Epoch: 1 [640/60000 (1%)]\tLoss: 2.246165\n",
      "Train Epoch: 1 [1280/60000 (2%)]\tLoss: 2.187228\n",
      "Train Epoch: 1 [1920/60000 (3%)]\tLoss: 2.095065\n",
      "Train Epoch: 1 [2560/60000 (4%)]\tLoss: 1.913412\n",
      "Train Epoch: 1 [3200/60000 (5%)]\tLoss: 1.631691\n",
      "Train Epoch: 1 [3840/60000 (6%)]\tLoss: 1.260106\n",
      "Train Epoch: 1 [4480/60000 (7%)]\tLoss: 0.818625\n",
      "Train Epoch: 1 [5120/60000 (9%)]\tLoss: 0.721219\n",
      "Train Epoch: 1 [5760/60000 (10%)]\tLoss: 0.639697\n",
      "Train Epoch: 1 [6400/60000 (11%)]\tLoss: 0.545805\n",
      "Train Epoch: 1 [7040/60000 (12%)]\tLoss: 0.602220\n",
      "Train Epoch: 1 [7680/60000 (13%)]\tLoss: 0.404711\n",
      "Train Epoch: 1 [8320/60000 (14%)]\tLoss: 0.470617\n",
      "Train Epoch: 1 [8960/60000 (15%)]\tLoss: 0.316652\n",
      "Train Epoch: 1 [9600/60000 (16%)]\tLoss: 0.353487\n",
      "Train Epoch: 1 [10240/60000 (17%)]\tLoss: 0.412354\n",
      "Train Epoch: 1 [10880/60000 (18%)]\tLoss: 0.245503\n",
      "Train Epoch: 1 [11520/60000 (19%)]\tLoss: 0.294931\n",
      "Train Epoch: 1 [12160/60000 (20%)]\tLoss: 0.168844\n",
      "Train Epoch: 1 [12800/60000 (21%)]\tLoss: 0.417805\n",
      "Train Epoch: 1 [13440/60000 (22%)]\tLoss: 0.227437\n",
      "Train Epoch: 1 [14080/60000 (23%)]\tLoss: 0.262678\n",
      "Train Epoch: 1 [14720/60000 (25%)]\tLoss: 0.367240\n",
      "Train Epoch: 1 [15360/60000 (26%)]\tLoss: 0.191997\n",
      "Train Epoch: 1 [16000/60000 (27%)]\tLoss: 0.378696\n",
      "Train Epoch: 1 [16640/60000 (28%)]\tLoss: 0.304443\n",
      "Train Epoch: 1 [17280/60000 (29%)]\tLoss: 0.215771\n",
      "Train Epoch: 1 [17920/60000 (30%)]\tLoss: 0.439348\n",
      "Train Epoch: 1 [18560/60000 (31%)]\tLoss: 0.308354\n",
      "Train Epoch: 1 [19200/60000 (32%)]\tLoss: 0.351393\n",
      "Train Epoch: 1 [19840/60000 (33%)]\tLoss: 0.240488\n",
      "Train Epoch: 1 [20480/60000 (34%)]\tLoss: 0.309650\n",
      "Train Epoch: 1 [21120/60000 (35%)]\tLoss: 0.238529\n",
      "Train Epoch: 1 [21760/60000 (36%)]\tLoss: 0.191429\n",
      "Train Epoch: 1 [22400/60000 (37%)]\tLoss: 0.073127\n",
      "Train Epoch: 1 [23040/60000 (38%)]\tLoss: 0.424991\n",
      "Train Epoch: 1 [23680/60000 (39%)]\tLoss: 0.233289\n",
      "Train Epoch: 1 [24320/60000 (41%)]\tLoss: 0.282877\n",
      "Train Epoch: 1 [24960/60000 (42%)]\tLoss: 0.178173\n",
      "Train Epoch: 1 [25600/60000 (43%)]\tLoss: 0.307530\n",
      "Train Epoch: 1 [26240/60000 (44%)]\tLoss: 0.198656\n",
      "Train Epoch: 1 [26880/60000 (45%)]\tLoss: 0.152297\n",
      "Train Epoch: 1 [27520/60000 (46%)]\tLoss: 0.348348\n",
      "Train Epoch: 1 [28160/60000 (47%)]\tLoss: 0.170641\n",
      "Train Epoch: 1 [28800/60000 (48%)]\tLoss: 0.128406\n",
      "Train Epoch: 1 [29440/60000 (49%)]\tLoss: 0.193024\n",
      "Train Epoch: 1 [30080/60000 (50%)]\tLoss: 0.107417\n",
      "Train Epoch: 1 [30720/60000 (51%)]\tLoss: 0.243982\n",
      "Train Epoch: 1 [31360/60000 (52%)]\tLoss: 0.189444\n",
      "Train Epoch: 1 [32000/60000 (53%)]\tLoss: 0.132585\n",
      "Train Epoch: 1 [32640/60000 (54%)]\tLoss: 0.261911\n",
      "Train Epoch: 1 [33280/60000 (55%)]\tLoss: 0.233286\n",
      "Train Epoch: 1 [33920/60000 (57%)]\tLoss: 0.109700\n",
      "Train Epoch: 1 [34560/60000 (58%)]\tLoss: 0.331924\n",
      "Train Epoch: 1 [35200/60000 (59%)]\tLoss: 0.183430\n",
      "Train Epoch: 1 [35840/60000 (60%)]\tLoss: 0.138651\n",
      "Train Epoch: 1 [36480/60000 (61%)]\tLoss: 0.225164\n",
      "Train Epoch: 1 [37120/60000 (62%)]\tLoss: 0.104253\n",
      "Train Epoch: 1 [37760/60000 (63%)]\tLoss: 0.149157\n",
      "Train Epoch: 1 [38400/60000 (64%)]\tLoss: 0.189433\n",
      "Train Epoch: 1 [39040/60000 (65%)]\tLoss: 0.250426\n",
      "Train Epoch: 1 [39680/60000 (66%)]\tLoss: 0.249523\n",
      "Train Epoch: 1 [40320/60000 (67%)]\tLoss: 0.183520\n",
      "Train Epoch: 1 [40960/60000 (68%)]\tLoss: 0.245599\n",
      "Train Epoch: 1 [41600/60000 (69%)]\tLoss: 0.060219\n",
      "Train Epoch: 1 [42240/60000 (70%)]\tLoss: 0.195216\n",
      "Train Epoch: 1 [42880/60000 (71%)]\tLoss: 0.275590\n",
      "Train Epoch: 1 [43520/60000 (72%)]\tLoss: 0.232538\n",
      "Train Epoch: 1 [44160/60000 (74%)]\tLoss: 0.076090\n",
      "Train Epoch: 1 [44800/60000 (75%)]\tLoss: 0.069422\n",
      "Train Epoch: 1 [45440/60000 (76%)]\tLoss: 0.106610\n",
      "Train Epoch: 1 [46080/60000 (77%)]\tLoss: 0.179241\n",
      "Train Epoch: 1 [46720/60000 (78%)]\tLoss: 0.182599\n",
      "Train Epoch: 1 [47360/60000 (79%)]\tLoss: 0.188973\n",
      "Train Epoch: 1 [48000/60000 (80%)]\tLoss: 0.163096\n",
      "Train Epoch: 1 [48640/60000 (81%)]\tLoss: 0.112224\n",
      "Train Epoch: 1 [49280/60000 (82%)]\tLoss: 0.127071\n",
      "Train Epoch: 1 [49920/60000 (83%)]\tLoss: 0.044716\n",
      "Train Epoch: 1 [50560/60000 (84%)]\tLoss: 0.108146\n",
      "Train Epoch: 1 [51200/60000 (85%)]\tLoss: 0.258518\n",
      "Train Epoch: 1 [51840/60000 (86%)]\tLoss: 0.129650\n",
      "Train Epoch: 1 [52480/60000 (87%)]\tLoss: 0.089145\n",
      "Train Epoch: 1 [53120/60000 (88%)]\tLoss: 0.137788\n",
      "Train Epoch: 1 [53760/60000 (90%)]\tLoss: 0.079945\n",
      "Train Epoch: 1 [54400/60000 (91%)]\tLoss: 0.277009\n",
      "Train Epoch: 1 [55040/60000 (92%)]\tLoss: 0.038963\n",
      "Train Epoch: 1 [55680/60000 (93%)]\tLoss: 0.116265\n",
      "Train Epoch: 1 [56320/60000 (94%)]\tLoss: 0.141395\n",
      "Train Epoch: 1 [56960/60000 (95%)]\tLoss: 0.091779\n",
      "Train Epoch: 1 [57600/60000 (96%)]\tLoss: 0.040374\n",
      "Train Epoch: 1 [58240/60000 (97%)]\tLoss: 0.029758\n",
      "Train Epoch: 1 [58880/60000 (98%)]\tLoss: 0.107635\n",
      "Train Epoch: 1 [59520/60000 (99%)]\tLoss: 0.060310\n",
      "\n",
      "Test set: Average loss: 0.1038, Accuracy: 9673/10000 (97%)\n",
      "\n",
      "Train Epoch: 2 [0/60000 (0%)]\tLoss: 0.234685\n",
      "Train Epoch: 2 [640/60000 (1%)]\tLoss: 0.072973\n",
      "Train Epoch: 2 [1280/60000 (2%)]\tLoss: 0.047250\n",
      "Train Epoch: 2 [1920/60000 (3%)]\tLoss: 0.090135\n",
      "Train Epoch: 2 [2560/60000 (4%)]\tLoss: 0.072432\n",
      "Train Epoch: 2 [3200/60000 (5%)]\tLoss: 0.157780\n",
      "Train Epoch: 2 [3840/60000 (6%)]\tLoss: 0.043005\n",
      "Train Epoch: 2 [4480/60000 (7%)]\tLoss: 0.046215\n",
      "Train Epoch: 2 [5120/60000 (9%)]\tLoss: 0.049275\n",
      "Train Epoch: 2 [5760/60000 (10%)]\tLoss: 0.104608\n",
      "Train Epoch: 2 [6400/60000 (11%)]\tLoss: 0.048932\n",
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      "Train Epoch: 2 [28160/60000 (47%)]\tLoss: 0.079348\n",
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      "Train Epoch: 2 [30080/60000 (50%)]\tLoss: 0.117308\n",
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      "Train Epoch: 2 [42880/60000 (71%)]\tLoss: 0.232693\n",
      "Train Epoch: 2 [43520/60000 (72%)]\tLoss: 0.144979\n",
      "Train Epoch: 2 [44160/60000 (74%)]\tLoss: 0.240821\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 2 [44800/60000 (75%)]\tLoss: 0.007890\n",
      "Train Epoch: 2 [45440/60000 (76%)]\tLoss: 0.041299\n",
      "Train Epoch: 2 [46080/60000 (77%)]\tLoss: 0.099569\n",
      "Train Epoch: 2 [46720/60000 (78%)]\tLoss: 0.042829\n",
      "Train Epoch: 2 [47360/60000 (79%)]\tLoss: 0.073301\n",
      "Train Epoch: 2 [48000/60000 (80%)]\tLoss: 0.125005\n",
      "Train Epoch: 2 [48640/60000 (81%)]\tLoss: 0.042513\n",
      "Train Epoch: 2 [49280/60000 (82%)]\tLoss: 0.208839\n",
      "Train Epoch: 2 [49920/60000 (83%)]\tLoss: 0.188321\n",
      "Train Epoch: 2 [50560/60000 (84%)]\tLoss: 0.094078\n",
      "Train Epoch: 2 [51200/60000 (85%)]\tLoss: 0.125364\n",
      "Train Epoch: 2 [51840/60000 (86%)]\tLoss: 0.062559\n",
      "Train Epoch: 2 [52480/60000 (87%)]\tLoss: 0.136570\n",
      "Train Epoch: 2 [53120/60000 (88%)]\tLoss: 0.035366\n",
      "Train Epoch: 2 [53760/60000 (90%)]\tLoss: 0.038643\n",
      "Train Epoch: 2 [54400/60000 (91%)]\tLoss: 0.009318\n",
      "Train Epoch: 2 [55040/60000 (92%)]\tLoss: 0.083935\n",
      "Train Epoch: 2 [55680/60000 (93%)]\tLoss: 0.074104\n",
      "Train Epoch: 2 [56320/60000 (94%)]\tLoss: 0.032243\n",
      "Train Epoch: 2 [56960/60000 (95%)]\tLoss: 0.081518\n",
      "Train Epoch: 2 [57600/60000 (96%)]\tLoss: 0.034120\n",
      "Train Epoch: 2 [58240/60000 (97%)]\tLoss: 0.045129\n",
      "Train Epoch: 2 [58880/60000 (98%)]\tLoss: 0.026470\n",
      "Train Epoch: 2 [59520/60000 (99%)]\tLoss: 0.041290\n",
      "\n",
      "Test set: Average loss: 0.0617, Accuracy: 9804/10000 (98%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "use_cuda = not args.no_cuda and torch.cuda.is_available()\n",
    "\n",
    "torch.manual_seed(args.seed)\n",
    "\n",
    "device = torch.device(\"cuda\" if use_cuda else \"cpu\")\n",
    "\n",
    "kwargs = {'num_workers': 1, 'pin_memory': True} if use_cuda else {}\n",
    "train_loader = torch.utils.data.DataLoader(\n",
    "    datasets.MNIST('../data', train=True, download=False,\n",
    "                   transform=transforms.Compose([\n",
    "                       transforms.ToTensor(),\n",
    "                       transforms.Normalize((0.1307,), (0.3081,))\n",
    "                   ])),\n",
    "    batch_size=args.batch_size, shuffle=True, **kwargs)\n",
    "test_loader = torch.utils.data.DataLoader(\n",
    "    datasets.MNIST('../data', train=False, transform=transforms.Compose([\n",
    "                       transforms.ToTensor(),\n",
    "                       transforms.Normalize((0.1307,), (0.3081,))#给定均值和标准差\n",
    "                   ])),\n",
    "    batch_size=args.test_batch_size, shuffle=True, **kwargs)\n",
    "\n",
    "\n",
    "model = Net().to(device)\n",
    "optimizer = optim.SGD(model.parameters(), lr=args.lr, momentum=args.momentum)\n",
    "#moment）通过引入一个新的变量 v 去积累之前的梯度（通过指数衰减平均得到），得到加速学习过程的目的。\n",
    "\n",
    "for epoch in range(1, args.epochs + 1):\n",
    "    train(args, model, device, train_loader, optimizer, epoch)\n",
    "    test(args, model, device, test_loader)\n",
    "\n",
    "if (args.save_model):\n",
    "    torch.save(model.state_dict(),\"mnist_cnn.pt\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    " for data, target in train_loader:\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "output = model(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([64, 1, 28, 28])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fa42f757b38>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b=data[0][0]\n",
    "b=b.reshape(1, 1, 28, 28)\n",
    "plt.imshow(b[0][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[9]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output = model(b)\n",
    "pred = output.argmax(dim=1, keepdim=True)\n",
    "pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 20, 24, 24])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = b\n",
    "x = F.relu(model.conv1(x))\n",
    "x.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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v2rTJiO1ZR06eDG2xDnIYL92JHMCKTuQAVnQiB1RsG93uzx4/fnxm226j9+tnPoz1wQcfGPGqVauM2B6/fvDgwcy23cc+cOBAI7b7yffsMVdu7tq1qxHbY+eJisEzOpEDWNGJHMCKTuSAimmjp1a//cjo0aOzxnab3NvGBoB169YZ8Zo1a3Lu37FjR2b71VdfNfaNGzfOiO3nz+1+9A8//BBEYeMZncgBrOhEDmBFJ3JAxbTRBw0aZMRnnnmmEZ9++umZ7W3bthn7tm7dasRvv/22EdvHe9vkAFBVVZXZPvvss3Pm8dZbbxnxoUOHQFRqPKMTOYAVncgBZXvpbj8Oak/31LNnTyP2dmu9+eabxr7333/fiO1Lc/vRUXvqKe+w1wsvvDDrPsCcdgo49ZFXuyvv+PHjIAqKZ3QiB7CiEzkg76W7iDwIYCqAJlUdkX6tB4DHANQA2AzgBlXlY1YEADhx4gT2798fuJyZM2eGkE3KsGHDQinH7qEJ4vDhw4HLWL9+va/j/LTRHwIwD8AvPa/NAVCnqnPT62XPATC7wBwDGTJkiBH36dPHiL3daYDZ7raHvHqnggJObRePHDnSiO37Ad6pp+ypouw87V+ufa/Bvh+wffspqx8RFSzvpbuqLgawx3p5GoD56e35AK4POS8iClGxbfRqVW0+De4AUJ3rYCKKV+DuNVVVEcm6eqZ3OV0iikexFb1RRPqqaoOI9AWQdR0h73K6uf5DyMeegtlug5977rlG3Lp1ayP2TtlsD5e1p53yLoMMAO3atTPivn37GnGvXr0y2/a9AvumlP0Y6u7du434xIkTIApbsZfuCwHMSG/PAPB0OOlQ0ojIABF5SUTWisgaEbk97pyocHkruogsALAUwBAR2SYiMwHMBTBZRDYAuDIdU2U6DuBOVR0GYByA20QknL4qikzeS3dVnZ5l16SQc6EESt90bUhv7xeRegD9AKzN+YOUKGUz1t2eKspug9vt6i5duhixd7rnnTt3GvvsR0XtdrT93meccYYRe9v4dh+8Pb2z/cirnUsYA01KRURqAIwEsCzeTKhQHAJLvohIJwBPALhDVfe1sH+WiKwQkRX2vPgUP1Z0yktEWiNVyR9R1SdbOkZVa1V1tKqOthehoPixolNOkmq3PACgXlXvjTsfKk7ZtNHttq29nLDdZr/sssuM2Nv3bY9tt58Jt5dgOnr0qBG3amX+/9itW7fMdmNjo7HPfgiivr7eiO3pn+1x+AkwHsAtAN4UkebFuL+uqs/FmBMVqGwqOsVDVZcAkLwHUqLx0p3IAazoRA4om0t3ux392muvGbHdt20/B+5t+9r94kuXLjXiDRs2GLG9hJN9V9k755w955v9PLk9lbSdC1EplE1Fp/Jx+PDhU9anK0aY/fHnnXdeKOXcfPPNoZQDABdddFHgMl588UVfx/HSncgBZXtG37hxoxH/z//8jxG/8sorRux9fNQe8nrkyBEjtqdoPnbsmBHbj616p4+2p4Kyu9P27TMHldlTTROVAs/oRA5gRSdyACs6kQPKto1us9vZy5b5f5LSO80UALRp08aI7a69wYMHG7G3C81+zHT16tVGbN8f4NRRFAWe0YkcwIpO5ABWdCIHVEwbPQj7kVc7rqmpMWJ7xJZ3+ii7H92eSsqepoooCjyjEzmAFZ3IAazoRA5gGx3AwIEDjbh3795GbC8HZY+z9459tx9TZb85JQHP6EQOYEUncgArOpEDnGyjd+rUyYjtqaHOOeccI7aXWbKne37nnXcy2/a01Amcvpkc5GRFp9Lau3cvHnvsscDl3HrrrSFkk+J3yqV8Nm3aFEo5APDUU08FLsMekJWNn2WTW1wfW0R6iMgLIrIh/Xf3fGURUTz8tNGzrY89B0Cdqg4GUJeOiSiB/KyPnm197GkAJqYPmw9gEYDZJckyZPaSyt7lmoBTx7bbz5jbc8Z5+87tZ9mJkqCgu+7W+tjV6f8EAGAHgOpQMyOi0Pi+GWevj+1deEBVVUQ0y8/NAjAraKJEVDxfFT3L+tiNItJXVRtEpC+AFm//qWotgNp0OS3+ZxA1u8vL7m579913jdjuTrNXTPVO2Vyp3WkiUgVgBYDtqjo17nyoMH7uumdbH3shgBnp7RkAng4/PUqQ2wHU5z2KEslPG715fewrRGRl+s8UAHMBTBaRDQCuTMdUgUSkP4BPAvh53LlQcfzcdc+1PvakcNOhhLoPwN0AOmc7wHsvxp5Vl+Ln5Mg4eyooe2po75BWABg0aJAR28Nc9+7dm9mutDa6iEwF0KSqr4nIxGzHee/FdOnSJRH3YugjfKiF8hkP4DoR2QzgUaSacA/HmxIVihWdclLVr6lqf1WtAXATgBdVNby1gykSrOhEDnCyjW7bvHlzzti75BIANDQ0GLE9PXSlUtVFSA11pjLDMzqRA1jRiRzAik7kALGXBC7pm4nsBLAFQC8Au/IcHodKyutMVe2d/7DweX7PuSTts05aPoC/nHz9niOt6Jk3FVmhqqMjf+M8mFd0kvZvSlo+QLg58dKdyAGs6EQOiKui18b0vvkwr+gk7d+UtHyAEHOKpY1ORNHipTuRA1jRiRwQaUUXkWtE5C0R2Sgisc4DLyIPikiTiKz2vBbrohQuLJaRpO9AOp8WP/O4iUiViPxVRJ4No7zIKnp6csH7AVwLYBiA6emFIOLyEIBrrNfiXpSiohfLSOB3AMj+mcct1Dn6ojyjjwWwUVU3qepRpCYxmBbh+xtUdTGAPdbL05BajALpv6+POKcGVX09vb0fqV9082IZseUVokR9B4Ccn3lsSjFHX5QVvR+ArZ54G2L+QFuQmEUpKnSxjER/B6zPPE7Nc/SF9vwzb8Zloal+x1j6Hu3FMpKSVyXL9ZlHnEdmjr4wy42yom8HMMAT90+/liSN6cUokGtRilLKtVhGnHmFJJHfgSyfeVxKMkdflBV9OYDBInKWiLRBav6xhRG+vx+xLkrhwGIZifsO5PjMY1GyOfpUNbI/AKYAWA/gbQD3RPneLeSyAKlVYo8h1VacCaAnUne1NwD4E4AeEec0AanL8lUAVqb/TIk7r0r9DuT6zOPOK53bRADPhlEWh8ASOSDQpXvSBj8QUcuKPqOnBz+sBzAZqUvf5QCmq+ra8NIjojAEme45M/gBAESkefBD1oqelGWTXaGq2dbMKykRUXup6WJ07x7eSN8TJ06EUs7AgQNDKQc4dWmwYuzevRv79+/P+3sOUtFbGvxwcYDyqEK0atXqlDXni3HdddeFkE2Kdw37IO6///5QygGAP/zhD4HL+Pd//3dfx5V8AQfvKptEFI8gFd3X4Af1rLLJS3eieARpSCVu8AMRtazoiq6qxwF8CcDzSD3x87iqrgkrMUoOdqOWv0BtdFV9DsBzIeVCCeR5hjzTjSoiC9mNWl64mmrIzjnnHCM+77zzjHj37t1GvGXLlpxxAhTcjUrJw8dUKZ9EP0NO/vCMTqHwdqOmHgijJGFFD1nXrl2NuH///kZ8/vnnG3FdXZ0R26OlwhroEUDB3ahVVVXsRk0YXrpTPuxGrQA8o1NOqnpcRJq7UasAPMhu1PLDik55sRu1/LGiF2H0aHPJau+jvnb32d69e43YbsOfe+65Rrxt2zYjTkAbnSoA2+hEDmBFJ3IAL90pdP3798c999wTuJwzzjgjhGxS9u/fH0o5hw4dCqUcALj33uCTzjY2Nvo6jhW9BX369DHiT33qU0bcu3dvI/Z+2PX15nJZ27ebXc6dO3c24h07dhjxwYMHC0uWyAdeuhM5gBWdyAGs6EQOYBsdwKhRo4x45syZRnzRRRcZ8WmnmR/bE088kdm2b/rY/epbt2414l27dhnxhx9+6CNjosLwjE7kAFZ0IgewohM5wMk2+oUXXmjEs2fPNuIhQ4YY8bFjx4z4f//3f434oYceymzbK4LU1NQYcb9+5uQsAwYMMOK1a80ZmvwOiCDKhWd0IgewohM5gBWdyAHOtNG9c7f98Ic/NPadddZZRrxv3z4j/u53v2vETz31lO/3tceyT5o0yYj37NljxEePHvVdNpFfPKMTOYAVncgBzly6z5s3L7M9dOhQY9+BAweM+O677zbiIOtYT58+3YjHjRtnxHZ3mv0IrD0VFVExeEYncgArOpED8l66i8iDAKYCaFLVEenXegB4DEANgM0AblBVXmMSgNTowDCaHKtXrw4hm5QZM2aEUs53vvOdUMoBgOuvvz5wGQ888ICv4/y00R8CMA/ALz2vzQFQp6pz0+tlzwEwu4WfjY09rHXEiBGZbXverzlzzCW/g7TJJ0yYYMTXXnutEVdXVxux3b3WqhUvsih8eb9VqroYwB7r5WkA5qe35wMI/l8TEZVMsaePalVtSG/vAFCd62Aiilfg7jVVVRHJunqmdzldIopHsRW9UUT6qmqDiPQF0JTtQO9yurn+QwiqW7duRmw/iuqd0ul3v/udsc87FVQxrrzyysz2DTfcYOy77LLLjPj111834ldffdWI161bFygXopYUe+m+EEDzbcwZAJ4OJx1KGhEZICIvichaEVkjIrfHnRMVLm9FF5EFAJYCGCIi20RkJoC5ACaLyAYAV6ZjqkzHAdypqsMAjANwm4gMizknKlDeS3dVnZ5l16Qsr1MFSd90bUhv7xeRegD9AKzN+YOUKBUz1n348OFGbE+j7B3A8bOf/aygsgcNGpQz9i6j/LGPfczYZy/vZE/3vGHDhoJyiZOI1AAYCWBZC/syN13t+yUUP47OIF9EpBOAJwDcoar77P2qWquqo1V1dMeOHaNPkHJiRae8RKQ1UpX8EVV9Mu58qHCs6JSTiAiABwDUq2rwdX4pFhXTRt+yZYsRv/nmm0bsfe7bbkMOHDjQiO32vqrZ/W9P6ey9H3Dy5Elj3+bNm43YflBj06ZNSLjxAG4B8KaIrEy/9nVVfS7GnKhAFVPRqTRUdQkAiTsPCoaX7kQOYEUnckDZXrrb/dMdOnQw4hdffNGIDx48mNm2nwk/55xzjLhdu3ZGvHHjRiN+7733jNg71t1eYmnFihU5Y3u+OqJSKNuKTsl18uTJUNZ5/9GPfhRCNilf/OIXQynHvskbxOLFiwOXYU9ckg0v3YkcUDZn9J49exqxfeluj8b64IMPjNh7Se1dtQU49X/FP/3pTzn325f+EydOzGzb3Wv2GSDMedCI/OIZncgBrOhEDmBFJ3JA2bTR7Sma7XnDjx8/bsT2tMn79+/PbL/xxhvGvlWrVhWUy+WXX27E3iG19uqpdjcfu9MoDjyjEzmAFZ3IAazoRA4omza6PdLK7ic/cuSIEVdVVRmxt42+b98pE6QUxDvkFQDGjh2b2f71r39t7LOncyaKA8/oRA5gRSdyACs6kQPKpo1ue//99yN7ry996UtGPG3aNCP2Lvf06KOPGvuOHj1ausSIfOIZncgBrOhEDmBFJ3JA2bbRS6l169ZGPGbMGCPu0aOHEf/2t7/NbNvTThElASs6ha5Pnz746le/GricZctOWeKtaN/61rdCKefCCy8MpRwAaGpqCq2sfPwsm9zi+tgi0kNEXhCRDem/u5c+XSIqhp82erb1secAqFPVwQDq0jERJZCf9dGzrY89DcDE9GHzASwCMLskWUbMHss+cuRII66vrzfil156KbO9ffv20iVGVKSC7rpb62NXp/8TAIAdAKqz/BgRxcx3Rc+1PramViHULD83S0RWiMiKlvZTeRCRKhH5q4g8G3cuVDhfd92zrI/dKCJ9VbVBRPoCaPEWoqrWAqhNl9PifwZJM2jQICP2PuIKAK+99poR19XVlTynBLgdQD2ALnEnQoXzc9c92/rYCwHMSG/PAPB0+OlREohIfwCfBPDzuHOh4vg5o7e4PjaAuQAeF5GZALYAuKE0KVIC3AfgbgCd406EiuPnrnuu9bEnhZsOJY2ITAXQpKqvicjEHMfNAjALOHWhSYofR8YBGDp0qBF7HzsFgEWLFhnxT37yEyO2p56uMOMBXCciUwC0A9BFRB5W1Zu9B3nvxYwaNaos7sW4hA+1UE6q+jVV7a+qNQBuAvCiXckp+VjRiRzAS3fyTVUXITUCksqMkxXdfszUXpK5ffv2RvzUU08Z8dYKLrXBAAAgAElEQVStW0uTGFGJ8NKdyAGs6EQOYEUncoCknkeJ6M1EdiI1iq4XgF2RvbF/lZTXmarauxTJ5OP5PeeStM86afkA/nLy9XuOtKJn3lRkhaqOjvyN82Be0Unavylp+QDh5sRLdyIHsKITOSCuil4b0/vmw7yik7R/U9LyAULMKZY2OhFFi5fuRA6ItKKLyDUi8paIbBSRWKeHFpEHRaRJRFZ7Xot1rnoX5tBP0ncgnU+Ln3ncwp6jL7KKLiJVAO4HcC2AYQCmp+eHj8tDAK6xXot7rvqKnkM/gd8BIPtnHrfmOfpCEeUZfSyAjaq6SVWPAngUqbnhY6GqiwHssV6ehtQc9Uj/fX3EOTWo6uvp7f1I/aKb59CPLa8QJeo7AOT8zGNTijn6oqzo/QB4H/vahpg/0BYkZq76Cp1DP9HfAeszj1PzHH0nwyqQN+OyyDVXfakVO4c+FS/XZx5xHpk5+sIsN8qKvh2Ad9bA/unXkqQxPUc9cs1VX0q55tCPM6+QJPI7kOUzj0vzHH2bkWraXCEiDwctNMqKvhzAYBE5S0TaIDX/2MII39+PWOeqd2AO/cR9B3J85rEo2Rx9qhrZHwBTAKwH8DaAe6J87xZyWYDU4pHHkGorzgTQE6m72hsA/AlAj4hzmoDUZfkqACvTf6bEnVelfgdyfeZx55XObSKAZ8MoiyPjiBzAm3FEDghU0ZM2yomIWlb0pXt6lNN6AJORauMuBzBdVdfm+Bm2EyKkqtmW0iqpsH7PrVqFd8HZv3//UMpp165dKOUAQOfOwZey27x5M3bt2pX39xxkuufMKCcAEJHmUU5ZKzpRITp27BhaWbNnzw6lHHv5riCuuOKKwGWMHu1vApog/2X6GuUkIrNEZIWIrAjwXkQUQMkXcFDP4nu8dCeKR5AzeiJHORHRqYJU9MSNciKilhVd0VX1OIAvAXgeqUf7HlfVNWElRsnBbtTyF6iNrqrPAXgupFwogTyTRWS6UUVkYa5uVEoeJ1dTLaWuXbsacevWrY34xIkTRrx3796S5xQQu1ErAIfAUj7sRq0APKNTKNiNmmys6EXo1888oXXv/tGkrL169TL2pR53/sg777xjxMeOHTPiAwcOhJFimNiNWgF46U75sBu1AvCMTjmp6nERae5GrQLwILtRyw8rOuXFbtTyx4regj59+hjxRRddZMT2U1XeLrPGxsacx9qPS+7evbvoPIn8YhudyAGs6EQO4KU7ha5169andDMWo02bNiFkkzJmzJhQynnxxRdDKQcAzj333MBl2N2z2bCiAxg3bpwRT5gwwYiHDx9uxB06dDDil156KbNt95Pv22cu+rF2rTly9Pjx44UlS1QEXroTOYAVncgBrOhEDnCyjf53f/d3RnzeeecZ8bRp5pLd9rTDzz//vBF7x7O/9957xr4dO3YUnSdRWHhGJ3IAKzqRA1jRiRzgTBvd2+6+7rrrjH1Tpkwx4vXr1xtxbW2tEb/yyitG/NZbb4WRIlHJ8IxO5ABWdCIHsKITOaBi2+j2+PVbb701s33NNdcY+1577TUj/uY3v2nEdXV1vt+3d+/eRnzVVVcZ8YoV5iSpbN9TFHhGJ3IAKzqRAyrm0v2CCy4w4jvuuMOIvZfrGzduNPbdc889Rux97LRQ9uL29qW8Pdx2+3Zz5uQETvdMFYBndCIHsKITOSDvpbuIPAhgKoAmVR2Rfq0HgMcA1ADYDOAGVU38aoEUjbZt2+Lss88OXI7d+xHEvHnzQiln2LBhoZQDAG+88UbgMg4dOuTrOD9t9IcAzAPwS89rcwDUqerc9HrZcwDMLjDHQKqqqoz405/+tBFffvnlRvzhhx9mtu+9915jX5A2OQB8/vOfz2zb00516tTJiO2pptgmpyjkvXRX1cUA9lgvTwMwP709H8D1IedFRCEq9q57tao2pLd3AKjOdqCIzAIwq8j3IaIQBO5eU1XNtUwul9Mlil+xFb1RRPqqaoOI9AXQFGZSfnz84x83YnvZJHtK5rlz52a2H3jggYLey+4L/+QnP2nEV199dWbbHl779NNPG/Hy5csLeu+4icgApO7PVANQALWq+t/xZkWFKrZ7bSGAGentGQCeznEslbfjAO5U1WEAxgG4TUTCu/VMkchb0UVkAYClAIaIyDYRmQlgLoDJIrIBwJXpmCqQqjao6uvp7f0A6gH0izcrKlTeS3dVnZ5l16SQc6GEE5EaACMBLIs3EypU2Yx1r642b+zba2nZyxH/3//9nxH//Oc/9/1eQ4cONWJvGxwAxo8fb8QDBgzIbB8+fNjYZ/fR29NBlwsR6QTgCQB3qOq+FvZnelfatm0bcXaUD4fAUl4i0hqpSv6Iqj7Z0jGqWquqo1V1dOvWraNNkPJiRaecJLU6xQMA6lX13nzHUzKxolM+4wHcAuAKEVmZ/jMl3w9RsiS2jW5f/o0aNcqIzzjjDCPesmWLEb/88stGnKvdOHbsWCO+5ZZbjLhv375GvH//fiNuavpoGMG2bduMfYsXL876vuVAVZcAkLwHUqLxjE7kAFZ0IgewohM5ILFt9EGDBhnxwIEDjbhjx45GvGeP+SStt91sH28/q37llVca8aZNm4z4L3/5ixH36dPHiL33D+w2uV0WURwSW9GpfHXu3BkTJ04MXM4zzzwTPJm0b3/726GU06ZNm1DKAYBrr702cBn2zd9seOlO5IDEntFT4zSyx0ePHjViewpn79RRgHm53b59e2PfE088YcT19fVGPHLkSCPu3r171lzWrFkDoqThGZ3IAazoRA5gRSdyQGLb6Lt27TJie5pke0ir3e627456y7O73nbu3JkzF3tqaXv5J2+b/d13381ZFlEceEYncgArOpEDWNGJHFA2bfQVK1YY8d695lJvPXv2NGL7UdLdu3dntvO1ye1llCZNMqfHmzp1qhF7p6liG52SiGd0IgewohM5gBWdyAGJbaPbvG3sluJ27doZsT023u860gDwT//0T0Z81113GbE9bdX8+fNBlGQ8oxM5gBWdyAGs6EQOKJs2ej72UkiF+PSnP23El112mRF37tzZiO3n1+1n4YmSpmIqOiXHwYMHTxngVIzHHnsshGxSvvOd74RSzvvvvx9KOQCwfv36wGUcOXLE13F+lk0eICIvichaEVkjIrenX+8hIi+IyIb0393zlUVE8fDTRj8O4E5VHQZgHIDbRGQYgDkA6lR1MIC6dExECeRnffQGAA3p7f0iUg+gH4BpACamD5sPYBGA2SXJMmR2n7t32WMAuPDCC43YnmnzD3/4Q2kSIyqRgtroIlIDYCSAZQCq0/8JAMAOANVZfiazbjYRxcN395qIdEJqjew7VHWfd5+qKgBt6ee862YHypRiJSJVIvJXEXk27lyocL7O6CLSGqlK/oiqPpl+uVFE+qpqg4j0BdCUvYRkGT3a/D9n8ODBRty1a1cjvv/++43YXrnFEbcDqAfQJe5EqHB+7roLgAcA1KvqvZ5dCwHMSG/PAPB0+OlREohIfwCfBPDzfMdSMvk5o48HcAuAN0VkZfq1rwOYC+BxEZkJYAuAG0qTIiXAfQDuBtA534GUTH7uui8BIFl2T8ryOlUIEZkKoElVXxORiTmOy9x0tXs1KH7OjIzr169fZnv48OHGvl69ehnxkiVLjNhuoztmPIDrRGQKgHYAuojIw6p6s/cgVa0FUAsAXbt2bfHGLMWHD7VQTqr6NVXtr6o1AG4C8KJdySn5WNGJHODMpTsFp6qLkBoBSWXGmYru7Ru3p5myh7i+8sorRrx9+/bSJUYUAV66EzmAFZ3IAazoRA6Q1PMoEb2ZyE6kRtH1ArArz+FxqKS8zlTV3qVIJh/P7zmXpH3WScsH8JeTr99zpBU986YiK5L4NBvzik7S/k1JywcINydeuhM5gBWdyAFxVfTamN43H+YVnaT9m5KWDxBiTrG00YkoWrx0J3JApBVdRK4RkbdEZKOIxDo9tIg8KCJNIrLa81qsc9W7MId+kr4D6Xxa/MzjFvYcfZFVdBGpAnA/gGsBDAMwPT0/fFweAnCN9Vrcc9VX9Bz6CfwOANk/87g1z9EXiijP6GMBbFTVTap6FMCjSM0NHwtVXQxgj/XyNKTmqEf67+sjzqlBVV9Pb+9H6hfdPId+bHmFKFHfASDnZx6bUszRF2VF7wdgqyfehpg/0Bb4mqs+CsXMoV8GEv0dsD7zODXP0XcyrAJ5My6LXHPVl1qxc+hT8XJ95hHnkZmjL8xyo6zo2wF41z7qn34tSRrTc9Qjrrnqc82hH2deIUnkdyDLZx6X5jn6NiPVtLlCRB4OWmiUFX05gMEicpaItEFq/rGFEb6/H7HOVe/AHPqJ+w7k+MxjUbI5+lQ1sj8ApgBYD+BtAPdE+d4t5LIAqcUjjyHVVpwJoCdSd7U3APgTgB4R5zQBqcvyVQBWpv9MiTuvSv0O5PrM484rndtEAM+GURZHxhE5INCle9IGPxBRy4o+o6cHP6wHMBmpS9/lAKar6trw0iOiMASZBTYz+AEARKR58EPWit6rVy8dOHBggLckv959913s2rUr21JaJXXaaadp27ZtA5dTXR3ecIGDBw+GUs77778fSjkA0Lt38AmA9u7di4MHD+b9PQep6C0Nfrg41w8MHDgQixcvDvCW5NfHP/7x2N67bdu2GDYs+CjSr3zlKyFkk7J8+fJQylm4MLxOgi9+8YuBy5g3b56v40revSYis0RkhYis2LUraVNyEbkhSEX3NfhBVWtVdbSqjrYXMySiaASp6Ikb/EBELSu6oqvqcQBfAvA8Uk/8PK6qa8JKjJKD3ajlL9Daa6r6HIDnQsqFEsjzDHmmG1VEFrIbtbw4s8hiLseOHTPil19+2Yhra2tz7t+376OHnXr27Gnsu/XWW434/PPPN+IxY8YYcZ8+fYy4qqoqW9pRKbgblZKHj6lSPol+hpz84RmdQiEiswDMAoA2bdrEnA3ZnKnoJ09+NFnHunXrjH2PPPKIEf/oRz8q+n12795txP/5n/9pxJdeeqkRv/XWW0Y8Y8YMI7Yv5WPguxsV6XnIO3bsyCelEoaX7pQPu1ErgDNndCqOqh4XkeZu1CoAD7IbtfywolNe7EYtfxVb0b1tcgCoq6vLbH/1q1819r399tuR5AQAQ4YMMeLPfOYzRrx3714jPv300zPbrVqxpUXF4TeHyAGs6EQOqNhLd4rP8ePHEcYjyV/4whdCyCZl+PDhoZSzY8eOUMoBgF/96leBy7C7c7OpmIpuzyDym9/8xoi//OUvR5lOVr/4xS+MuFu3bkb8L//yL0Z8+PDhzHaHDh1KlxhVNF66EzmAFZ3IAazoRA4o2zb6iRMnjHj+/PlGPHv27CjTKdozzzxjxLfddpsR9+/fP7N94MCBSHKiysMzOpEDWNGJHMCKTuSAsm2jb99uPhL9ve99L6ZMgtm4caMRf+5znzPiJ554IrPNfnQqFs/oRA5gRSdyACs6kQPKpo1uPyTx/e9/34jDXOUyTocOHTLipqamzHZNTU3E2VCl4BmdyAGs6EQOSOyl+9GjR434d7/7nRHbQ17L1X/9138Z8RVXXGHEAwcOjDIdqlA8oxM5gBWdyAF5L91F5EEAUwE0qeqI9Gs9ADwGoAbAZgA3qOrebGWQW8477zysWLEicDnz5s0LIZuU3r17h1LOTTfdFEo5wKlPYBZD1d+iOH7a6A8BmAfgl57X5gCoU9W56fWy5wAI9blQe6mir33ta2EWnxh33XWXEdtDeb3zprVr1y6SnKjy5L10V9XFAPZYL08D0Hw3bD6A60POi4hCVGwbvVpVG9LbOwBUh5QPEZVA4JtxmmokZG0oiMgsEVkhIivCmAKYiApXbD96o4j0VdUGEekLoCnbgd7ldEeNGuV7Od2lS5casXfa40q2atUqI/aOJ2AbnYpV7Bl9IYDmhbxnAHg6nHQoaURkgIi8JCJrRWSNiNwed05UuLwVXUQWAFgKYIiIbBORmQDmApgsIhsAXJmOqTIdB3Cnqg4DMA7AbSIyLOacqEB5L91VdXqWXZNCzoUSKH3TtSG9vV9E6gH0A7A21sSoIIkd675kyZK4U4iFPQBiz56Peja7dOkSdToGEakBMBLAslgToYJxCCz5IiKdADwB4A5V3dfC/kzvys6dO6NPkHJiRae8RKQ1UpX8EVV9sqVjVLVWVUer6uiwhptSeFjRKScREQAPAKhX1XvjzoeKk9g2ehgD/stB+/btjbhXr15GbC+rHIPxAG4B8KaIrEy/9nVVfS7GnKhAia3olAyqugSAxJ0HBcNLdyIHsKITOSCxl+5nnnlm3ClE4uqrrzbi4cOHG3HXrl2jTIcqVGIrOpWvjRs3Ytq0aYHLsf8TDGLGjBn5D/IhzJzCeJqzqqrK13G8dCdyQGLP6OPHjzfiH//4xzFlUlrnnnuuEV9yySVGnOrGJgqGZ3QiB7CiEzmAFZ3IAWXTRv/sZz9rxL/85S9RjoYOHWrEO3bsMOIBAwZEmQ45gmd0IgewohM5gBWdyAGJbaPbQz+/853vGPHFF19sxAsWLDDidevWGXFS5pS/8cYbjdjuN2/Tpk2U6ZAjeEYncgArOpEDWNGJHJDYNro9xrt79+5GfMsttxjxlClTjLixsdGIDxw4kNmeOXOmsW/Lli1F55nPhRdeaMTe6ZsBYNy4cSV7b6JmPKMTOYAVncgBrOhEDkhsGz0fuw1vT5Nsx88//3xmu5RtcttFF11kxFdeeaUR+50hhCiIsq3olFwdO3bEmDFjApfj/c85qDvuuCOUcn7zm9+EUg4AtG7dOnAZftc/8LNscovrY4tIDxF5QUQ2pP/unq8sIoqHnzZ6tvWx5wCoU9XBAOrSMRElkJ/10bOtjz0NwMT0YfMBLAIwuyRZhqCuri6S97H7ze3nz+2x7URRKOiuu7U+dnX6PwEA2AGgOtTMiCg0vit6rvWxVVUBaJafy6ybnZQnyKhwIlIlIn8VkWfjzoUK5+uue5b1sRtFpK+qNohIXwBNLf2sqtYCqAWAUaNGtfifQRTee++9SN7H7j6zL93t1VPLyO0A6gF0iTsRKpyfu+7Z1sdeCKB5+YsZAJ4OPz1KAhHpD+CTAH4edy5UHD9n9BbXxwYwF8DjIjITwBYAN5QmRUqA+wDcDaBz3IlQcfzcdc+1PvakcNOhpBGRqQCaVPU1EZmY47hZAGYBXBgyiZwZGdejR4+SlX3GGWdktrdv327sO//880v2vhEZD+A6EZkCoB2ALiLysKre7D3Iey+mX79+sd2LoZbxoRbKSVW/pqr9VbUGwE0AXrQrOSUfKzqRA5y5dKfgVHURUiMgqcw4U9FL2Va+6qqrMtv2Y6mlvDdA5Bcv3YkcwIpO5ABWdCIHSOp5lIjeTGQnUqPoegFI4hMulZTXmarauxTJ5OP5PeeStM86afkA/nLy9XuOtKJn3lRkhaqOjvyN82Be0Unavylp+QDh5sRLdyIHsKITOSCuil4b0/vmw7yik7R/U9LyAULMKZY2OhFFi5fuRA5gRSdyQKQVXUSuEZG3RGSjiMQ6D7yIPCgiTSKy2vNarItSuLBYRpK+A+l8WvzM4xb2ZJyRVXQRqQJwP4BrAQwDMD29EERcHgJwjfVa3ItSVPRiGQn8DgDZP/O4NU/GGYooz+hjAWxU1U2qehTAo0gtAhELVV0MYI/18jSkFqNA+u/rI86pQVVfT2/vR+oX3bxYRmx5hShR3wEg52cem1JMxhllRe8HYKsn3oaYP9AWJGZRigpdLCPR3wHrM49T82ScJ8MqkDfjssi1KEWpFbtYBhUv12cecR6ZyTjDLDfKir4dwABP3D/9WpI0phejQK5FKUop12IZceYVkkR+B7J85nFpnoxzM1JNmytE5OGghUZZ0ZcDGCwiZ4lIG6QmGlwY4fv7EeuiFA4slpG470COzzwWJZuMU1Uj+wNgCoD1AN4GcE+U791CLguQWiX2GFJtxZkAeiJ1V3sDgD8B6BFxThOQuixfBWBl+s+UuPOq1O9Ars887rzSuU0E8GwYZXEILJEDAl26J23wAxG1rOgzenrww3oAk5G69F0OYLqqrg0vPSIKQ5DpnjODHwBARJoHP2St6CLCdkKEVDXbmnklVVVVpaedFnwm8bZt24aQTcqhQ4dCKefss88OpRwAaGoK3nly8OBBHDlyJO/vOchvo6XBDxfbB3kX3yM3nHbaaejbt2/gcgYNGhRCNimrV6/Of5APtbXhPbZ+//33By7jhRde8HVcyRdwUM/iezyjE8UjyM24RA5+IKJTBanoiRv8QEQtK7qiq+pxAF8C8DxST/w8rqprwkqMkoPdqOUvUBtdVZ8D8FxIuVACeZ4hz3SjishCdqOWF2dWUw2iS5cuRuxdPRUALr/88sz2+PHjjX2bN2824j/+8Y9GvGTJEiPesGGDER85cqSgXEug4G5USh4+pkr5JPoZcvKHZ3QKhXe8RFVVVczZkI0VHakBHl6jR5vLXY0bN86IJ02aZMQ1NTWZ7a5duxr7Ro4cacS7dplr5h08eNCI9+0z5zx49913s2QdGV/dqN7xEm3btuV4iYThpTvlw27UCsAzOuWkqsdFpLkbtQrAg+xGLT+s6JQXu1HLn5MV3W5He7vHAGDy5MlGfNlllxnxzp07jfjHP/5xZtt+Iun00083YvtG1bZt23Ie/95772W2jx8/DqJisI1O5ABWdCIHOHnpTqV15plnYt68eYHLWbFiRQjZpPzlL38JpZy9e/eGUg4AHD58OHAZJ0/6W+PBmYruncTg4ovN+TE+/elPG7G3XxwA6urqjPinP/2pEa9fv953Hm3atDHiTp06GXGHDh2MuFUrXnRRcPwWETmAFZ3IAazoRA6o2Da6PbGgt11+yy23GPt69uxpxL/+9a+N+OmnzRWQNm7cWHReR48eNeI9e8yVm99//30j9nuzhSgXntGJHMCKTuQAVnQiB1RsG93uf/aOZ9+6daux78knzSWxH3/8cSO2nxHPxV5d5BOf+IQRv/rqq0Y8YMAAIz527JgRb9q0KbMdxgALchPP6EQOYEUncgArOpEDKqaNPmTIECO+9tprjbhPnz6Z7SeeeMLYZ/eTF9Imt5177rlG/Pd///dG3LlzZyN+4403jNh+5pz96BQGntGJHMCKTuSAsr1079WrlxEPHDjQiG+44QYjXrx4cWb7zTffNPYVeqneu3dvI54wYUJm+9ZbbzX2nXnmmUb8zDPPGLE99VS7du2M+MSJEwXlRtQSntGJHMCKTuSAvJfuIvIggKkAmlR1RPq1HgAeA1ADYDOAG1Q1vDl2qKxt374d3/zmNwOXU19fH0I2KYcOHQqlnC1btoRSDnDqbMTF8Lv8lZ82+kMA5gH4pee1OQDqVHVuer3sOQBmF5hjIP36mev8XXnllUZs/2JfeumlzPbKlSsLeq8RI0YY8dVXX23E11xzTWbbbmPb3WerVq0yYvuX3bFjRyP2PsbK9joVK++lu6ouBrDHenkagPnp7fkArg85LyIKUbFt9GpVbUhv7wBQHVI+RFQCgbvXVFVFJOvqmd7ldIkoHsVW9EYR6auqDSLSF0BTtgO9y+nm+g+hUGeccYYR29NBLViwwIhzzcd91VVXGfH48eON+IILLjDiLl26GPH27R+tImy3o1955RUjXrduXdY8iEql2Ev3hQBmpLdnAHg6x7FUxkRkgIi8JCJrRWSNiNwed05UuLwVXUQWAFgKYIiIbBORmQDmApgsIhsAXJmOqTIdB3Cnqg4DMA7AbSIyLOacqEB5L91VdXqWXZNCzoUSKH3TtSG9vV9E6gH0A7A21sSoIGU71t1uJ9tTNNlTMnXr1i2zfeONNxr7rrvuOiO2l2TasGGDEdv98N6pqexx8Pb0zuVMRGoAjASwrIV9mZuu9rJTFD8OgSVfRKQTgCcA3KGqpzwFpKq1qjpaVUefdlrZnj8qFis65SUirZGq5I+o6pP5jqfkYUWnnEREADwAoF5V7407HypO2V5j2f3Tu3fvNuL+/fsb8emnn57ZPu+884x9u3btMuL777/fiJctM5ukdl+593l0b586cOrY9jI0HsAtAN4UkeabE19X1edizIkKVLYVnaKhqksASNx5UDC8dCdyACs6kQPK5tK9Q4cORmwvq2Rbv3591njJkiWBcrHH1Xfv3j2zbc9H99577wV6L6IwlE1Fp/JRXV2Nr3zlK4HL+d73vhdCNikLFy4MpZybb745lHIAYMyYMYHL8DtmgZfuRA4omzN6kkZb/eM//qMRv/3225ntJOVJ1IxndCIHsKITOYAVncgBZdOgPHLkiBHbbWF7FdIwfeELXzDiTp06GfGf//znzHa+bj+iOPCMTuQAVnQiB7CiEzmgbNvobdu2NeJSttHt+wHPP/+8Ebdqxf8vKdn4DSVyACs6kQNY0YkcUDZtdJvdZrfbyXacqw1vPwJ72223GfH5559vxDt37jTiRYsW5cyVKG48oxM5gBWdyAGs6EQOKNs2uu3kyZM541zs6Z8vueQSI7aXe2psbCwwO6J4VUxFp+Ro1aoV2rVrF7icZ555JoRsUgYOHBhKOWHeeB01alTgMvbv3+/rOD/LJre4PraI9BCRF0RkQ/rv7vnKIqJ4+GmjZ1sfew6AOlUdDKAuHRNRAvlZHz3b+tjTAExMHzYfwCIAs0uSZYkNGjTIiO3lnezln4JOF00UtYLuulvrY1en/xMAgB0AqkPNjIhC47ui51ofW1UVgGb5uVkiskJEVgTKlGIlIlUi8lcReTbuXKhwvu66Z1kfu1FE+qpqg4j0BdDU0s+qai2A2nQ5Lf5nELcdO3YY8be+9S0jtoe8Oup2APUAusSdCBXOz133bOtjLwQwI709A8DT4adHSSAi/QF8EsDP486FiuPnjN7i+tgA5gJ4XERmAtgC4IbSpEgJcB+AuwF0jteasgQAACAASURBVDsRKo6fu+651seeFG46lDQiMhVAk6q+JiITcxw3C8AsAOjdu3dE2ZFfHBkH4KWXXoo7hSQbD+A6EZkCoB2ALiLysKoaqw1678Wcc845ibwX4zI+1EI5qerXVLW/qtYAuAnAi3Ylp+RjRSdyAC/dyTdVXYTUCEgqM05W9K5duxrxBx98EFMmRNHgpTuRA1jRiRzAik7kAEk9jxLRm4nsRGoUXS8AuyJ7Y/8qKa8zVTWWkSue33MuSfusk5YP4C8nX7/nSCt65k1FVqjq6MjfOA/mFZ2k/ZuSlg8Qbk68dCdyACs6kQPiqui1Mb1vPswrOkn7NyUtHyDEnGJpoxNRtHjpTuSASCu6iFwjIm+JyEYRiXV6aBF5UESaRGS157VY56p3YQ79JH0H0vm0+JnHLew5+iKr6CJSBeB+ANcCGAZgenp++Lg8BOAa67W456qv6Dn0E/gdALJ/5nFrnqMvFFGe0ccC2Kiqm1T1KIBHkZobPhaquhjAHuvlaUjNUY/039dHnFODqr6e3t6P1C+6eQ792PIKUaK+A0DOzzw2pZijL8qK3g/AVk+8DTF/oC1IzFz1FTqHfqK/A9ZnHqfmOfr8rxSaB2/GZZFrrvpSK3YOfSpers884jwyc/SFWW6UFX07gAGeuH/6tSRpTM9Rj1xz1ZdSrjn048wrJIn8DmT5zOPSPEffZqSaNleIyMNBC42yoi8HMFhEzhKRNkjNP7Ywwvf3I9a56h2YQz9x34Ecn3ksSjZHn6pG9gfAFADrAbwN4J4o37uFXBYgtXjkMaTaijMB9ETqrvYGAH8C0CPinCYgdVm+CsDK9J8pcedVqd+BXJ953Hmlc5sI4NkwyuLIOCIHBLp0T9rgByJqWdFn9PTgh/UAJiN16bscwHRVXRteekQUhiCzwGYGPwCAiDQPfsha0ZO6mmqlUtVsS2mVVKdOnbRHjx6By9mzxx7PVLz27duHUk6YOZ133nmBy9i6dSt2796d9/ccpKK3NPjh4gDlUYXo0aMH7r777sDlPPLIIyFkk3LBBReEUs6CBQtCKQcA/vjHPwYu46qrrvJ1XMnndfcuvkdE8QhS0X0NflDP4nu8dCeKR5C77okb/EBELSv6jK6qx0XkSwCeB1AF4EFVXRNaZkQUmkD96Kr6nKp+TFXPVtX/L6ykKFk4XqL88ek1yimhk0VQgZxcTbWUqqvNR8VbtTL/L21oaECZKXi8BCUPz+iUj6/JIkRkloisEJEVBw4ciCw58ocVnUKhqrWqOlpVR3fq1CnudMjCS/ciVFVVZY3btGlj7BsyZIgRl+GleyIni6DC8IxO+XC8RAXgGZ1y4niJysCKTnmp6nMAnos7DyoeK3oLunc3F0I5duyYEdt3lU+cOJHZ3rp1q7HPfkLp0KFDRjxq1Kii8yTyi210IgewohM5gJfuFLpt27bhzjvvDFzOM888E0I2KWHNDHPxxeHNrXLJJZcELmPbtm2+jmNFB9CvnznQa/v24ruJhw4dasTvvPOOEdtDZImiwEt3IgewohM5gBWdyAFOttE7dOhgxHab/Ctf+YoRd+nSxYi//e1vG/HJkx+tbrtu3Tpj36c+9Skj/od/+AcjHjFihBGvXr06W9pEReMZncgBrOhEDmBFJ3KAk210u6/7E5/4hBHbz5Q/9NBDRmxPD+Vto9vsse3nnnuuEd933305cyUKA8/oRA5gRSdyACs6kQOcaaP/4Ac/yGzbz5svXbrUiBcuNGdKamxsLPp9p0+fbsQbNmwouiyiYvGMTuQAVnQiB1TspfsXvvAFI1b9aMXmN99809j3s5/9rGR5vPzyy0b85S9/uWTvRZQNz+hEDshb0UXkQRFpEpHVntd6iMgLIrIh/Xf3XGUQUbz8XLo/BGAegF96XpsDoE5V56aX0Z0DYHb46VE5GjFiRCjTQP32t78NIZsUe3WdYtlPNgbxq1/9KnAZ//qv/+rruLwVXVUXi0iN9fI0ABPT2/MBLELMFb2mpsaIW7dubcT79+/PbG/evDmCjFL+9m//1ojvvvtuI549m/8/UukV20avVtXmRcR2AOBEaEQJFviuu6qqiGi2/SIyC8CsoO9DRMUr9ozeKCJ9ASD9d1O2A73L6Rb5XkQUULFn9IUAZgCYm/776dAyKtIXv/hFI96xY4cRr1+/PrP91FNPlSyPyZMnG/GYMWOM+LOf/WzJ3rsURGQAUjdiqwEogFpV/e94s6JC+eleWwBgKYAhIrJNRGYiVcEni8gGAFemY6pMxwHcqarDAIwDcJuIDIs5JyqQn7vu07PsmhRyLpRA6ZuuDent/SJSD6AfgLWxJkYF4cg48i3dzToSwLJ4M6FCVcxY99dff92I7emdStkunzp1amb7+9//vrHPnhp6wYIFJcujlESkE4AnANyhqvta2J/pXbGXuKL48YxOeYlIa6Qq+SOq+mRLx3h7V3r06BFtgpQXKzrlJCIC4AEA9ap6b9z5UHFY0Smf8QBuAXCFiKxM/5kSd1JUmIppo//xj3804ptuusmI27dvn9m2p2C2TZgwwYiXLFmS83jvmtlvv/22se/YsWM5fzbpVHUJAIk7DwqGZ3QiB7CiEzmAFZ3IARXTRj/tNPOfYs8DN2jQoMy2PQ7+pz/9qRHPmTOnoPeeMuWje1O///3vjX1hTp5AVKyKqeiUHFu3bg1lJhZ73fogli0LZzBfhw4dQikHAL7xjW8ELqOhoSH/QeClO5ETKuaMvnfv3pz7+/btm9kePHiwse+WW24p6L1mzJhhxHfddVdm+5133imoLKIo8IxO5ABWdCIHsKITOSCxbfQBAwYY8datWwOV9+c//znQz3vNnz/fiD//+c9ntu3htVFOLU2UDc/oRA5gRSdyACs6kQMS20a32+QDBw40YntEUCkfB7VHeV177bVG7O3D/8UvflGyPIiKxTM6kQNY0YkcwIpO5IDEttFt7777bmTvZc9iao+N//DDD434xhtvLHlOREHwjE7kAFZ0IgewohM5oGza6FHq3bu3Edvj148cORJlOkSBsaJT6A4fPowNGzYELuczn/lMCNmkNDY2hlLOyy+/HEo5wKnrAxZDVX0d52d99AEi8pKIrBWRNSJye/r1HiLygohsSP/dPWDORFQiftroxwHcqarDAIwDcJuIDAMwB0Cdqg4GUJeOiSiB8l66q2oDgIb09n4RqQfQD8A0ABPTh80HsAjA7JJkGbHJkycb8dixY404jBlOiaJUUBtdRGoAjASwDEB1+j8BANgBoDrLz2TWzSaiePjuXhORTkitkX2Hqu7z7tPUHYEW7wp4180OlCnFSkSqROSvIvJs3LlQ4Xyd0UWkNVKV/BFVfTL9cqOI9FXVBhHpC6CpVElG7eMf/7gR19XVGfGKFSuiTCcpbgdQD6BL3IlQ4fzcdRcADwCoV9V7PbsWAmie4HwGgKfDT4+SQET6A/gkgJ/HnQsVx88ZfTyAWwC8KSIr0699HcBcAI+LyEwAWwDcUJoUKQHuA3A3gM7ZDvDei2ndunVEaZFffu66LwEgWXZPCjcdShoRmQqgSVVfE5GJ2Y5T1VoAtQDQvn17f6M4KDIcGdeCH/zgB0bcrVs3I27Xrp0RHz58uOQ5xWg8gOtEZAqAdgC6iMjDqnpzzHlRAfhQC+Wkql9T1f6qWgPgJgAvspKXH1Z0Igfw0p18U9VFSI2ApDLDit6Cbdu2GfGyZctiyoQoHLx0J3IAKzqRA1jRiRwgfmeoCOXNRHYiNYquF4Bdkb2xf5WU15mq2jv/YeHz/J5zSdpnnbR8AH85+fo9R1rRM28qsiKJT7Mxr+gk7d+UtHyAcHPipTuRA1jRiRwQV0Wvjel982Fe0Unavylp+QAh5hRLG52IosVLdyIHRFrRReQaEXlLRDaKSKzTQ4vIgyLSJCKrPa/FOle9C3PoJ+k7kM6nxc88bmHP0RdZRReRKgD3A7gWwDAA09Pzw8flIQDXWK/FPVd9Rc+hn8DvAJD9M49b8xx9oYjyjD4WwEZV3aSqRwE8itTc8LFQ1cUA9lgvT0Nqjnqk/74+4pwaVPX19PZ+pH7RzXPox5ZXiBL1HQByfuaxKcUcfVFW9H4AtnribYj5A22Br7nqo1DMHPplINHfAeszj1PzHH3BF2dL4824LHLNVV9qxc6hT8XL9ZlHnEdmjr4wy42yom8HMMAT90+/liSN6TnqEddc9bnm0I8zr5Ak8juQ5TOPS/McfZuRatpcISIPBy00yoq+HMBgETlLRNogNf/Ywgjf349Y56p3YA79xH0HcnzmsSjZHH2qGtkfAFMArAfwNoB7onzvFnJZgNTikceQaivOBNATqbvaGwD8CUCPiHOagNRl+SoAK9N/psSdV6V+B3J95nHnlc5tIoBnwyiLI+OIHBDo0j1pgx+IqGVFn9HTgx/WA5iM1KXvcgDTVXVteOkRURiCzAKbGfwAACLSPPgha0UXEbYTIqSq2ZbSKqnTTjtN27ZtG7ico0ePhpBNSr9+4XTXt2/fPpRyAGDdunWhlOPn9xykorc0+OHiAOVRhWjbti2GDh0auJz33nsvhGxSvvGNb4RSzvnnnx9KOQBw8cXRVZeSz+vuXWWTiOIRpKL7GvygnlU2eelOFI8gd90TN/iBiFpWdEVX1eMAvgTgeaSe+HlcVdeElRglB7tRy1+gNrqqPgfguZByoQTyPEOe6UYVkYXsRi0vXGSxCF26dDHi1q1bZ7Z3794ddTqlVnA3KiUPH1OlfBL9DDn5wzM6hcLbjdqmTZuYsyEbK3oLunXrZsTDhw834mHDzCnFOnXqlNnes8ecnWrRokVGvGVLviXJEqfgbtSOHTuyGzVheOlO+bAbtQLwjE45qepxEWnuRq0C8CC7UcsPKzrlxW7U8udkRa+qqjJi+wGMkSNHGnHv3uby0/bP9+rVK7Ntt+dramqM+JlnnjHi119/PX/CRAGxjU7kAFZ0Igc4eelOpdWtWzf8zd/8TeByLrjgghCySWlsbAylnPvuuy+UcgDgJz/5SeAyvvvd7/o6zpmK3rFjx8z2RRddZOyz4w4dOhjx4cOHc5admjE4xe6D79mzpxE3NZlTsm/bti3nfqIw8NKdyAGs6EQOYEUnckDFttHttvGll16a2R47dqyx78SJE0Zs37g5dOiQEXvb5ACwb99Ha/LZj6m+8847RrxhwwYj5gIaFAWe0YkcwIpO5ABWdCIHVEwb3W432+3wSy65JLN95MgRY5/dBreninr//feNeOfOnUZst/Fz7bMXJbDLIioFntGJHMCKTuQAVnQiB1RMG/3cc881YvsZ84MHD2a2T548aezzjoP//9m79yipqit/4N9N834pzaNtaaRRUYP4RsVniMqMIhHNTJyQiSFrkZDJMhMzEycSXSszk99MQmZlYjJjMhNGiTgaHxNNROMjiiJRfNABVKCBBtIg2NAgIMi7Yf/+qOqyzqGr6lbdU/feqvP9rMXi7qrqU5vq2tx77j33HABYunSpEdv96C1btuSML7/8cuM5e3659evXH5M7Ublxj07kARY6kQcq9tD9hBNOMOIrrrjCiHv16pUzPnz4sPHc4sWLjdi+3GYPa92+fbsRn3XWWZlte/3s7t3Nj/jUU0814ra2NiPOd6mOqFTcoxN5gIVO5IGCh+4iMgfAZADtqjo2/VgtgEcBNAJoBXCzqu4sX5pUSfr06XPMbLil6OjocJBNiquZe+wuYxj2KMlS2N3QXIL00e8HcA+AB7IemwlgvqrOSq+XPRPAHUXmWBS7r2tPyWxP/5Q9BTNg9rvtW0XtfvGHH35oxPZUUtdcc40RZw+3tdcds9u2C8Duo69evRpErhU8dFfVhQB2WA9PATA3vT0XwI2O8yIih0rto9epaueuaAuAOkf5EFEZhL68pqoqIjmnScleTpeI4lFqoW8VkXpVbRORegA5z3RkL6eb7z+EQuyljUaPHm3E9jTLw4YNM+LsW1P37dtnPGcPS7VPAtnzi9u5ZJ8/OP30043n7D77ihXm+oStra0gKrdSD93nAZiW3p4G4Ek36VDSiMgIEXlZRFaKyAoRuS3unKh4BQtdRB4G8DqA00Vkk4hMBzALwEQRaQFwTTqm6tQB4FuqOgbAeAC3isiYAj9DCVPw0F1Vp+Z46mrHuVACpU+6tqW394hIM4DhAFbGmhgVpWLGutfW1uZ93p46yp4OKntgQe/evY3n7H70Rx99ZMR2f9++Rn/++edntu1ppv/whz8Y8caNG43YntYqyUSkEcB5AN6MNxMqFofAUiAi0h/A4wC+qaq7u3h+hog0iUhT9jz3lAwsdCpIRHogVeQPqeoTXb1GVWer6jhVHWcfTVH8WOiUl6Sm170PQLOq/jjufKg0FdNHt5cXLjS2/ZRTTjHi7Kmk7Bsc7HH0xx13nBEPGjTIiK+88kojzr7H/I033jCeW7nSPGdlj22vAJcBuAXAuyKyLP3Ynar6TIw5UZEqptApHqr6KgAp+EJKNB66E3mAhU7kgYo5dLdv0n/zTfNS7kknnWTE9rXx7OvXGzZsMJ6zly62++ijRo0yYnt66DVr1uTMyz63sHnzZhBFrWIKnSrHjh078Mgjj4Ruxx7YFMb3vvc9J+2MHDnSSTuAm5zsNQdz4aE7kQcqdo++ZMmSvM+/8MILRlxTU5PZtvcU9rBV+3Kb/b+mfejf1NSU2X733XeN5+zbUu1pqoiiwD06kQdY6EQeYKETeaBi++h2X3fBggVG3KNHDyPOviRm33QxdOhQI7722muNuLm52Yh37dplxFu3bs1s29NQuZi7mygs7tGJPMBCJ/IAC53IAxXbR7fZw1gPHTqUM96501wmzl5ied26dUZs39Z68sknG3F2/9/+2S1btuRLmygS3KMTeYCFTuQBFjqRB6qmjx6GPVXUgAEDjPiSSy4xYns66Pfeey+zvWzZMuO5o0ePukiRKBTu0Yk8wEIn8gALncgDXvbR7bHt9qwh5557rhHb19lXrVplxC0tLZntCpzOmTzgZaFTeXV0dGDbtm2h2zn77LMdZJPyv//7v07aGTt2rJN2AOCMM84I3UbQ6baCLJvc5frYIlIrIi+ISEv670GF2iKieATpo+daH3smgPmqOhrA/HRMRAkUZH30XOtjTwEwIf2yuQAWALijLFk6Vl9fb8T2ksz9+/c34v379xuxPY5++fLlDrMjcq+os+7W+th16f8EAGALgDqnmRGRM4ELPd/62Jq6dUxz/Fxm3exQmVKsRKRGRJaKyNNx50LFC3TWPcf62FtFpF5V20SkHkB7Vz+rqrMBzE630+V/BlE7cOCAEdu3uB4+fNiI7TPI2SuzAMfe9lqlbgPQDICLn1egIGfdc62PPQ/AtPT2NABPuk+PkkBEGgBcD+DeuHOh0gTZo3e5PjaAWQAeE5HpADYAuLk8KVIC/ATAtwEMKPRCSqYgZ93zrY99tdt0KGlEZDKAdlX9o4hMyPO6GQBmAMeOJKT4eTkyzu5jDxs2zIi7dTN7NHaf3l4R1b78VmUuA3CDiEwC0BvAQBF5UFW/kP2i7HMxAwcOTMS5GPoYb2qhvFT1O6raoKqNAD4H4CW7yCn5WOhEHvDy0J1Ko6oLkBoBSRWGhQ5g6dKlRtza2mrEDQ0NRmwv0USUdDx0J/IAC53IAyx0Ig+IPc67rG8msg2pUXRDAGyP7I2Dq6a8Rqrq0MIvcy/r95xP0j7rpOUDBMsp0O850kLPvKlIk6qOi/yNC2Be0Unavylp+QBuc+KhO5EHWOhEHoir0GfH9L6FMK/oJO3flLR8AIc5xdJHJ6Jo8dCdyAORFrqIXCsiq0VkrYjEOj20iMwRkXYRWZ71WKxz1fswh36SvgPpfLr8zOPmeo6+yApdRGoA/AzAdQDGAJianh8+LvcDuNZ6LO656qt6Dv0EfgeA3J953Drn6HMiyj36RQDWqup6VT0E4BGk5oaPhaouBLDDengKUnPUI/33jRHn1KaqS9Lbe5D6RXfOoR9bXg4l6jsA5P3MY1OOOfqiLPThAN7Lijch5g+0C4mZq75K59BP9HfA+szj1DlH31FXDfJkXA755qovt1Ln0KfS5fvMI84jM0efy3ajLPTNAEZkxQ3px5Jka3qOeuSbq76c8s2hH2dejiTyO5DjM49L5xx9rUh1ba4SkQfDNhploS8GMFpERolIT6TmH5sX4fsHEetc9R7MoZ+470CezzwWZZujT1Uj+wNgEoA1ANYBuCvK9+4il4eRWjzyMFJ9xekABiN1VrsFwIsAaiPO6XKkDsvfAbAs/WdS3HlV63cg32ced17p3CYAeNpFWxwZR+QBnowj8kCoQk/aKCci6lrJh+7pUU5rAExEqo+7GMBUVV2Z62e6deumNTU1Jb0fFefIkSM4evRorqW0ysrVqrn9+/d30QwA4KSTTnLSjstVefbt2xe6jQ8//BD79+8v+HsOM91zZpQTAIhI5yinnIVeU1ODIUOGhHhLCmr79nhnRUqdzA7n3HPPdZBJys9+9jMn7axYscJJO8Cx04yX4oEHHgj0ujCH7oFGOYnIDBFpEpGmo0edDfQhoiKU/WScqs5W1XGqOs5evJCIohGm8hI5yomIjhWm0BM3yomIulZyoatqB4CvA3geqVv7HlNVd2cqKDF4GbXyhVpkUVWfAfCMo1wogbImi8hcRhWRefkuo1LycDVVAIcPHzbiDz74oOS2TjvtNCO2T0D27dvXiJcsWWLEAwYMMOJ+/fqVnIsjRV9GpeThaXAqJNGTRVAw3KOTEyIyA8CMuPOgrnlT6NmDddrbyzdvw4UXXmjEN9xwQ97Xb9y40Yj/5V/+xXlOIQW6jKqqs5FecMDVEFhyh4fuVAgvo1YBb/boVBpV7RCRzsuoNQDm8DJq5WGhU0G8jFr5qrbQ7Rtoytkvz/bKK68Y8fXXX2/EU6dONeJdu3YZ8WuvvZazvV69erlIkTzEPjqRB1joRB6o2kN3ik/Pnj3R0NAQup2WlhYH2aScc845Ttqxu2Jh3HTTTaHb6N27d6DXVU2h21P8fPjhh87aPvXUU43YHta6Zs2azPamTZuM5z7/+c8b8Ve+8hUjfuSRR4z48ssvN+J33303s713796AGROZeOhO5AEWOpEHWOhEHqjYPvqRI0eM2GWffPhw8+as7t3Nj8nuhxfD7md/+tOfNuKLLroo73sTlYJ7dCIPsNCJPMBCJ/JAxXYAw0z3ZDv99NONuE+fPkZs98k/+ugjZ+9te+utt4w4e1kil0sUkV+4RyfyAAudyAMsdCIPVEwf3b5v2+WCjY2NjUb8/PPPO2vbXhF03bp1Rmz3u9va2oyYy0yTC9yjE3mAhU7kgcQeuturpxw4cMBZ22PGjDHil156yVnbtmXLlhnxtGnTjPjv//7vjfjee+814meffTazXc7LelTduEcn8gALncgDBQ/dRWQOgMkA2lV1bPqxWgCPAmgE0ArgZlXdWb40qZKcfPLJmDt3buh21q9f7yCbFHtmn1Jt2LDBSTsA8Oqrr4ZuI2h3Lkgf/X4A9wB4IOuxmQDmq+qs9HrZMwHcUWSOebkc4goAl156aWZ73759xnP2+YByeu6554zYnvPLXqKJt6mSCwUP3VV1IYAd1sNTAHT+lz0XwI2O8yIih0rdXdSpaufIji0A6nK9MHuVTXtSRSKKRujKU1UFkHP1TFWdrarjVHUcC50oHqXu0beKSL2qtolIPYBo1jsKYdGiRZG8zxlnnGHEp5xyihHb1+x/8Ytf5G1vwIABme1+/fqFzK54IjICqfMzdUj9hz5bVX8aeSIUSqm72HkAOkd+TAPwpJt0KIE6AHxLVccAGA/gVhEZU+BnKGEKFrqIPAzgdQCni8gmEZkOYBaAiSLSAuCadExVSFXbVHVJensPgGYAw/P/FCVNwUN3VZ2a46mrHedCCScijQDOA/BmvJlQsXiR1rG6OvMCxO9+97tQ7WUPiIijj95JRPoDeBzAN1V1dxfPZ66unHDCCRFnR4XwNDgVJCI9kCryh1T1ia5ek3115fjjj482QSqIhU55iYgAuA9As6r+OO58qDQsdCrkMgC3ALhKRJal/0yKOykqDvvoXTjuuOOMuJjlnl555RWnuQRd/7pcVPVVABJrEhQa9+hEHmChE3mAhU7kgcT20RsaGow4zFLFxXK5BHNY2WPdiUqV2EKnytWvX79j1nkvxYoVKxxkk3LLLbc4aefP/uzPnLQDHDsRaCk6OjoCvY6H7kQeSOwevW/fvkZsr3i6evXqKNOJDe/hJxf4LSLyAAudyAMsdCIPJLaPvnfvXiMeOXKkEX/xi1804vnz5xvx5s2by5NYAfbqp0eOHCnq52tra12mQwSAe3QiL7DQiTzAQifyQGL76Hbf1l6q6OjRo0Zsj1iy++i///3vHWZnOuecczLba9asMZ7bv39/UW317NnTSU5E2bhHJ/IAC53IAyx0Ig8kto9us+/SaW1tNWK7Tz5o0CAjPumkkzLbdn+/WPb48+xr/sX2yYcOHRoqF6IguEcn8gALncgDLHQiD1RMH72Qw4cPG3F7u7mS85YtW0pu2+6T29e6w7Rtj40nKoeqKXRKjubmZlx88cWh23n88ccdZJOyYMECJ+0sXLjQSTvAsTdileLgwYOBXhdk2eQRIvKyiKwUkRUiclv68VoReUFEWtJ/DyrUFhHFI0gfvQPAt1R1DIDxAG4VkTEAZgKYr6qjAcxPx0SUQEHWR28D0Jbe3iMizQCGA5gCYEL6ZXMBLABwR1myjNmpp55qxPv27TPiYqaitpd7IopCUWfdRaQRwHkA3gRQl/5PAAC2AKjL8WNEFLPAhS4i/ZFaI/ubqro7+zlVVQCa4+dmiEiTiDTZd5xR5RCRGhFZKiJPx50LFS/QWXcR6YFUkT+kqk+kH94qIvWq2iYi9QDau/pZVZ0NYDYA9OjRo8v/k94tsAAAIABJREFUDJLOvvU0jD59+jhrK2K3AWgGMDDuRKh4Qc66C4D7ADSr6o+znpoHYFp6exqAJ92nR0kgIg0ArgcQfmkRikWQPfplAG4B8K6ILEs/dieAWQAeE5HpADYAuLk8KVIC/ATAtwFwIbgKFeSs+6sAJMfTV7tNh5JGRCYDaFfVP4rIhDyvmwFgBsBZcpLIm5FxgwcPzmx/8MEHkb1vr169InuvMrkMwA0iMglAbwADReRBVf1C9ouyz8X069evIs/FVDPe1EJ5qep3VLVBVRsBfA7AS3aRU/Kx0Ik84M2hO4WnqguQGgFJFcabQs/uo/fo0cN4LsxtpoXYU1oRxYGH7kQeYKETeYCFTuQBSd2PEtGbiWxDahTdEADbI3vj4Kopr5GqGstc0lm/53yS9lknLR8gWE6Bfs+RFnrmTUWaVHVc5G9cAPOKTtL+TUnLB3CbEw/diTzAQifyQFyFPjum9y2EeUUnaf+mpOUDOMwplj46EUWLh+5EHoi00EXkWhFZLSJrRSTW6aFFZI6ItIvI8qzHYp2r3oc59JP0HUjn0+VnHjfXc/RFVugiUgPgZwCuAzAGwNT0/PBxuR/AtdZjcc9VX9Vz6CfwOwDk/szj1jlHnxNR7tEvArBWVder6iEAjyA1N3wsVHUhgB3Ww1OQmqMe6b9vjDinNlVdkt7eg9QvunMO/djycihR3wEg72cem3LM0RdloQ8H8F5WvAkxf6BdSMxc9VU6h36ivwPWZx6nzjn6nM2PzpNxOeSbq77cSp1Dn0qX7zOPOI/MHH0u242y0DcDGJEVN6QfS5Kt6TnqkW+u+nLKN4d+nHk5ksjvQI7PPC6dc/S1ItW1uUpEHgzbaJSFvhjAaBEZJSI9kZp/bF6E7x9ErHPVezCHfuK+A3k+81iUbY4+VY3sD4BJANYAWAfgrijfu4tcHkZq8cjDSPUVpwMYjNRZ7RYALwKojTiny5E6LH8HwLL0n0lx51Wt34F8n3nceaVzmwDgaRdtcWQckQdCHbonbfADEXWt5D16evDDGgATkTr0XQxgqqqudJceEbkQZhbYzOAHABCRzsEPOQtdRDR17oPKLd03i+XDrq2t1YaGhtDtuPyuHDp0yEk7LmcMPnDgQOg2Dh8+jI6OjoIfVJhC72rww8X5fkBE0L27NzNMx6qjoyO2925oaMBTTz0Vup3evXs7yCblT3/6k5N2fvSjHzlpBwBWrVoVuo1169YFel3Zqy578T0iikeYQg80+EGzFt/r1q0bT/ETxSDMWffEDX4goq6VvEdX1Q4R+TqA5wHUAJijqiucZUZEzoS6jq6qz6jqaap6iqr+q6ukKFk4XqLy8RQ4jr2MM3DgQCPu1s38//DgwYNG/OGHH5YnMRy7IGTUsiaLyIyXEJF5HC9RWXibKhWSuMkiqHgsdCok0GQRIjJDRJpEpGnHDnviHoqbl4fu/fr1M2J7EM+ePXuM2D5Up2NlX0Y9++yzeRk1YbhHp0ISOVkEFYeFToVwvEQV8PLQnYLjeInq4E2hDxr08ZoH+/fvN57btWtX1OkEdvjw4cx2XJfaVPUZAM/E8ubkBA/diTzAQifygDeH7hSddevW4S//8i9Dt/Ob3/zGQTYpPXv2dNLOr3/9ayftAMCyZctCt/H5z38+0OuqptBramqMOLtPDgDbt2/PbGf3e5PO/ncRlYKH7kQeYKETeYCFTuSBiu2j27eWDhkyxIg3bdoUWS4zZnw8Jd64ceOM5/bu3WvEa9asMeI//vGPeePsa+dHjhwJlSf5i3t0Ig+w0Ik8wEIn8kDF9tHtARDt7eVbMvzyyy834v/3//6fEV9yySWZ7ffff994bvNm845O+7q4PSjE7odnx3FPK0WVi3t0Ig+w0Ik8wEIn8kDF9NHtPnnfvn2N+KOPPnL2XhdccIERf/WrXzXiffv2GfEtt9yS2X7zzTeN5zZu3FjUe9v/zqNHjxb180Rd4R6dyAMsdCIPJPbQ3V4dxT5Ud3k57dxzzzXiH/zgB0ZcW1trxHfffbcR/9///Z+zXA4dOmTEvKRGLnCPTuQBFjqRBwoeuovIHACTAbSr6tj0Y7UAHgXQCKAVwM2qurN8aVIlGTJkCL785S+Hbuf73/++g2xSHn30USft2F2rMFxeKSokSB/9fgD3AHgg67GZAOar6qz0MrozAdzhMrHevXsb8bZt25y13dDQYMRf+9rXjNi+Bfaf//mfjfipp55ylgtRFAoeuqvqQgD2qnlTAMxNb88FcKPjvIjIoVL76HWq2pbe3gKgzlE+RFQGoS+vqaqKSM7VM0VkBoAZuZ4novIrtdC3iki9qraJSD2AnBe1s5fT7datW+DldMs5bdLYsWON2L4mbw95dckeH3DppZca8YEDB4y4ubk5s+3yRBD5pdRD93kApqW3pwF40k06lDQiMkJEXhaRlSKyQkRuizsnKl7BQheRhwG8DuB0EdkkItMBzAIwUURaAFyTjqk6dQD4lqqOATAewK0iMibmnKhIBQ/dVXVqjqeudpwLJVD6pGtbenuPiDQDGA5gZayJUVESO9bd9WCC7Gvjq1atMp577rnnnL5XPhdddJERn3/++Ubc1NRkxEm6TVVEGgGcB+DN/K+kpOEQWApERPoDeBzAN1V1dxfPzxCRJhFpinLEFwXDQqeCRKQHUkX+kKo+0dVrVHW2qo5T1XH9+/ePNkEqiIVOeUmqz3MfgGZV/XHc+VBpEttHd03140v4ra2tkb3v2WefbcSnnnqqEffp08eI7evo3bt//Cvq6OhwnF0glwG4BcC7ItK5oPedqvpMHMlQabwpdCqNqr4KQAq+kBKNh+5EHmChE3nAm0P37GmUix0zbt8bb/ezly9fnvNn7T54Y2OjEX/wwQdG/OGHHxrxwYMHg6ZJlJM3hU7ROXr06DFz35fit7/9rYNsUuwbmUrl8kTupz71qdBtLFy4MNDreOhO5IHE7tHtaY7t2zsHDx5sxFdccYURjx492oizR2vt2bPHeM6+VXTQoEFGbA+ZffDBB3OljTFjzPs9Tj75ZCMeMGCAES9YsMCId+3aZcTZlwWJSsU9OpEHWOhEHmChE3kgsX30w4cP533evkw1btw4I77pppuMeMSIEZlte8XSTZs2GfE//dM/GfHjjz9uxHY/Opt96e3iiy82Yvvy2ZYtW4x47969OdsmKhX36EQeYKETeYCFTuSBxPbR7WWR7OvJixYtMmJ7GOpLL71kxNm3i9oTI9jTN7366qtGnK9Pbtu+fbsR9+rVK+972co5zTX5i3t0Ig+w0Ik8wEIn8kBi++jZUyh1xb7Ovnu3OTHps88+a8QrVqzIbA8cONB4Lt9tpkGMHDkysz158mTjOftup+wllgBg48aNod6bKAju0Yk8wEIn8gALncgDie2jF2Lfr15I9hhz1/3iUaNGZbbtKZnte9nt53m/OUWhYgudkmvz5s2YOXNm6HYKnZAtxjXXXOOknddee81JOwAwffr00G2sXBlsrcsgyyZ3uT62iNSKyAsi0pL+e1ChtogoHkH66LnWx54JYL6qjgYwPx0TUQIFWR891/rYUwBMSL9sLoAFAO4oS5YOuLzP255T7swzz8xs27Ofrlu3zojb29ud5UEUVFFn3a31sevS/wkAwBYAdU4zIyJnAp/tsNfHzr67TFVVRLo8fSwiMwDMCJsoEZUuUKHnWB97q4jUq2qbiNQD6PKYVFVnA5gNAN26dYvtWlKYlUj79u1rxFdeeaURZx+6//73vzee27ZtmxEXmiIrqUSkBkATgM2qOrnQ6ylZgpx1z7U+9jwA09Lb0wA86T49SpDbADQXfBUlUpA+euf62FeJyLL0n0kAZgGYKCItAK5Jx1SFRKQBwPUA7o07FypNkLPu+dbHvtptOpRQPwHwbQADcr2A52KSjSPjulBfX2/Ef/d3f2fEF154oRGvWbMms93S0mI8d+DAAcfZRUtEJgNoV9U/isiEXK9LyrkY6hpvaqFCLgNwg4i0AngEqS5c7sXnKJFY6JSXqn5HVRtUtRHA5wC8pKpfiDktKhILncgD3vTRs5ddtqeSPv300414ypQpRmwvwbx//34jzrcYvT0ktpKp6gKkhjpTheEencgDLHQiD7DQiTwgUU5lJCLbAGwAMATA9gIvj0M15TVSVYeWI5lCsn7P+STts05aPkCwnAL9niMt9MybijSp6rjCr4wW84pO0v5NScsHcJsTD92JPMBCJ/JAXIU+O6b3LYR5RSdp/6ak5QM4zCmWPjoRRYuH7kQeYKETeSDSQheRa0VktYisFZFY54EXkTki0i4iy7Mei3VRCh8Wy0jSdyCdT5efedxEpEZElorI0y7ai6zQ05ML/gzAdQDGAJiaXggiLvcDuNZ6LO5FKap6sYwEfgeA3J953JzO0RflHv0iAGtVdb2qHkJqEoMpBX6mbFR1IYAd1sNTkFqMAum/b4w4pzZVXZLe3oPUL7pzsYzY8nIoUd8BIO9nHptyzNEXZaEPB/BeVrwJMX+gXUjMohRVulhGor8D1mcep845+o66apAn43LQ1HXHWK492otlJCWvapbvM484j8wcfS7bjbLQNwMYkRU3pB9Lkq3pxSiQb1GKcsq3WEaceTmSyO9Ajs88LmWZoy/KQl8MYLSIjBKRnkjNPzYvwvcPItZFKTxYLCNx34E8n3ksyjZHn6pG9gfAJABrAKwDcFeU791FLg8jtUrsYaT6itMBDEbqrHYLgBcB1Eac0+VIHZa/A2BZ+s+kuPOq1u9Avs887rzSuU0A8LSLtjgElsgDoQ7dkzb4gYi6VvIePT34YQ2AiUgd+i4GMFVVV7pLj4hcCDPdc2bwAwCISOfgh5yFnmsNdSoPVc21Zl5Zde/eXXv16hW6HZdTZffr189JO4cOHXLSDgD06NEjdBsHDx5ER0dHwd9zmELvavDDxSHaoyrRq1cvjBkTfhTp0qVLHWSTctZZZzlpZ/Nmd1cD6+rCj3tauTLYAXTZF3DgKptE8QtT6IEGP2jWKps8dCeKR5iz7okb/EBEXSu50FW1A8DXATyP1B0/j6nqCleJUXLwMmrlC9VHV9VnADzjKBdKoKx7yDOXUUVkHi+jVhZvVlMtxrBhw4z4/PPPN2J79dVs69atM+K1a9ca8Zo1a4y4T58+Rrx3797AeUak6MuolDy8TZUKSfQ95BQM9+jkRPZl1J49e8acDdm8LPS+ffsa8RlnnGHEJ554ohF362Ye+OzcudOIR44cmdn++te/bjy3a9cuI160aJERr1hhnr9cvXq1EW/atAkxK/oyar9+/XgZNWF46E6F8DJqFfByj07BqWqHiHReRq0BMIeXUSsPC50K4mXUyudNoWdfMhs9erTxXENDgxHbJ5PsS2Cf+MQnjPicc87JbJ933nnGc8cff7wR23c/9e7dO2+cgD46VQH20Yk8wEIn8oA3h+4UnX379qGpqSl0Oz/5yU8cZJPyr//6r07aufPOO520AwCpCWjD+fd///dAr6vaQj/11FONOLsfPny4ObDL/sAHDTLXMLSvsx85csSIN2zYkNleuHCh8Zx9XdyeeeW9994zYnv4bXZunMiTSsVDdyIPsNCJPMBCJ/JA1fTRTznlFCM+4YQTjDj71lL7WvaZZ55pxIMHDzZi+9ZTu1/94IMfL41l99+LZZ8/YL+cXOAencgDLHQiD7DQiTxQsX10+9r3gQMHjNjuZ2dfv7bvRz98+LARv/3220Zs30P+1ltvFZdsEVwuEEDUiXt0Ig+w0Ik8wEIn8kDF9tHtKZfteMSIEUac3ae3p2C253V77rnnjLitra3kPAvp3t38FYwdO9aIly1bVrb3Jn9wj07kARY6kQcq5tDdHtLav39/Iz755JONeMeOHUa8ffv2zLY9ffPcuXON+OjRo0Xllr2Siz1NlX27rP3e9nBae9qqlpaWzHYCV3GhCsE9OpEHWOhEHih46C4icwBMBtCuqmPTj9UCeBRAI4BWADer6s5cbZBfxowZg0ceeSR0O9/4xjccZJPyu9/9zkk7LqeSuu6660K3EfTuxiB99PsB3APggazHZgKYr6qz0utlzwRwR5E55mVPuXTccccZsd33tfuv9pDYgwcPZrbtKZTtD8seIrtv3z4jHj9+vBF/+tOfzmxfcsklxnP2kFb7Ul5zc7MRf/DBB3nfm6gUBQ/dVXUhgB3Ww1MAdJ7BmgvgRsd5EZFDpfbR61S1cxTJFgB1jvIhojIIfXlNVVVEcnYUspfTJaJ4lFroW0WkXlXbRKQeQHuuF2Yvp5vvPwSbfb15wIABRjxkyJC8P2/3sy+++OLMtj2sdNSoUUa8cuVKI86+Tg4AU6ZMyfm8Pe3Uxo0bjfipp54yYrsPb59b4FRS5EKph+7zAExLb08D8KSbdChpRGSEiLwsIitFZIWI3BZ3TlS8goUuIg8DeB3A6SKySUSmA5gFYKKItAC4Jh1TdeoA8C1VHQNgPIBbRWRMzDlRkQoeuqvq1BxPXe04F0qg9EnXtvT2HhFpBjAcwMq8P0iJktix7nbf1L6d037e7tOfdNJJRrx169bMtn1t2p5iOXsZZAD40pe+ZMT2+YLsa/TZ7wMAL7zwghEvXrzYiO1lle3r6EkiIo0AzgPwZhfPZU661tfXR5oXFcYhsBSIiPQH8DiAb6rqbvt5VZ2tquNUdZy9dh3Fj4VOBYlID6SK/CFVfSLufKh4LHTKS1JT89wHoFlVfxx3PlSaxPbR7evJS5cuNWJ7WSX7unljY6MRZ0/pfOmllxrP2ePP7edbW1uNeOjQoUa8YMGCzPaPfvQj47mPPvrIiO0lmypgLPtlAG4B8K6IdA5AuFNVn4kxJypSYgudkkFVXwUgBV9IicZDdyIPsNCJPFAxh+7Z16oBYMmSJXlf/+qrrxpx9iUf+x7wq666yojtse72tfF33nnHiJ999tm8uWTr3bu3Ee/fvz/wzxKVqmIKnSpHnz59cNZZZ4Vu57Of/ayDbFLs//hLZU9CGsZPf/rT0G20t+e8n8zAQ3ciD3izR9+5c2eX28Cxh+LlZF82JIoC9+hEHmChE3mAhU7kAW/66OVUU1OT2baXjrKniiKKA/foRB5goRN5gIVO5AH20btgT1s1duxYI7ZHI2WPAnv++efLlxhRibhHJ/IAC53IAyx0Ig942Ue3l2C2l0EeOXKkEbe0tBixfatpoVtmieLGPTqRB1joRB5goRN5wJs+eq9evTLbI0aMMJ6rra01Ynvaqt27j1mYxLBt27bMtj3tdAVM50we8KbQKTq7du3Ck0+GX0n77rvvdpBNyi9/+Usn7UycONFJOwBw1113hW5j8uTJgV4XZNnkLtfHFpFaEXlBRFrSf3PBLaKECtJHz7U+9kwA81V1NID56ZiIEijI+ui51seeAmBC+mVzASwAcEdZsnSgR48eme3+/fsbz9n9ans66L179xqxPUVz9th49skpiYo6626tj12X/k8AALYAqHOaGRE5E7jQ862PraoKQHP83AwRaRKRplCZUqxEpEZElorI03HnQsULdNY9x/rYW0WkXlXbRKQeQJczyavqbACz0+10+Z9BFLJXNV2/fn3O54Bjp4O2L7fZq692dHS4SDHpbgPQDGBg3IlQ8YKcdc+1PvY8ANPS29MAhL+eQokkIg0Argdwb9y5UGmC7NG7XB8bwCwAj4nIdAAbANxcnhQpAX4C4NsABsSdCJUmyFn3fOtjX+02HUoaEZkMoF1V/ygiE/K8bgaAGQAwdOjQiLKjoLwcGWdPBRV0oTpPXQbgBhGZBKA3gIEi8qCqfiH7RdnnYk499dTYzsVQ13hTC+Wlqt9R1QZVbQTwOQAv2UVOycdCJ/KAl4fuVBpVXYDUCEiqMNyjE3mAhU7kARY6kQdY6EQekNT9KBG9mcg2pEbRDQGwPbI3Dq6a8hqpqrGMXMn6PeeTtM86afkAwXIK9HuOtNAzbyrSpKrjIn/jAphXdJL2b0paPoDbnHjoTuQBFjqRB+Iq9NkxvW8hzCs6Sfs3JS0fwGFOsfTRiShaPHQn8kCkhS4i14rIahFZKyKxTg8tInNEpF1Elmc9Futc9T7MoZ+k70A6ny4/87i5nqMvskIXkRoAPwNwHYAxAKam54ePy/0ArrUei3uu+qqeQz+B3wEg92cet845+pyIco9+EYC1qrpeVQ8BeASpueFjoaoLAeywHp6C1Bz1SP99Y8Q5tanqkvT2HqR+0Z1z6MeWl0OJ+g4AeT/z2JRjjr4oC304gPey4k2I+QPtQmLmqq/SOfQT/R2wPvM4dc7Rd9RVgzwZl0O+uerLrdQ59Kl0+T7ziPPIzNHnst0oC30zgOz1ihvSjyXJ1vQc9cg3V3055ZtDP868HEnkdyDHZx6Xzjn6WpHq2lwlIg+GbTTKQl8MYLSIjBKRnkjNPzYvwvcPIta56j2YQz9x34E8n3ksyjZHn6pG9gfAJABrAKwDcFeU791FLg8jtXjkYaT6itMBDEbqrHYLgBcB1Eac0+VIHZa/A2BZ+s+kuPOq1u9Avs887rzSuU0A8LSLtjgyjsgDPBlH5IFQhZ60UU5E1LWSD93To5zWAJiIVB93MYCpqroy188MGTJEGxsbS3o/Kk5rayu2b9+eaymtsurTp48OGBB+mTZ71dowRowYUfhFAfTp08dJOwCwYsUKJ+2oasHfc5h53TOjnABARDpHOeUs9MbGRjQ1cZn0KIwbF99kKQMGDMDNN4dfc/OJJ9xd6frhD3/opJ2zzjrLSTsAcMYZZzhrq5Awh+6BRjmJyAwRaRKRpm3btoV4OyIqVdlPxqnqbFUdp6rjuMomUTzCFHoiRzkR0bHCFHriRjkRUddKLnRV7QDwdQDPI3Vr32Oq6uY0IiUKL6NWvlCrqarqMwCecZQLJVDWZBGZy6giMi/fZVRKHi6bDODgwYNG/PTT5uw93/ve94z4nXfecfbeAwcONOKFCxca8TnnnOPsvUpU9GVUSh4OgaVCEj1ZBAXDQicnssdL7N+/P+50yOLNofvRox/PymOPzrvvvvuMeNGiRUa8fPlylMvu3eZkJvfcc48R/8///E/Z3jugQJdRVXU20gsODBs2jLdEJgz36FQIL6NWAW/26FQaVe0Qkc7LqDUA5vAyauVhoVNBvIxa+aq20LP75ADw29/+NrP9wAMPGM89+WRypmC7915zKu9//Md/zGw3NDREnQ5VCfbRiTzAQifyQNUeulPlGzlypLO23n33XSft/Pd//7eTdgDgpptuCt3Gyy+/HOh1VVPoe/bsMWL7F/KHP/whs/3UU09FkpMLvXv3jjsFqgI8dCfyAAudyAMsdCIPVGwfvaOjw4h/+ctfGrE9g+gbb7xR9pzKgSvpkAvcoxN5gIVO5AEWOpEHKraP/v777xtxfX29EVdqn9z23nsfT+7CefGpVNyjE3mAhU7kARY6kQcqpo9u98nnzp1rxN/97nejTCcy+/btizsFqgLcoxN5gIVO5IHEHrrbq6e8+eabRvzQQw9FmU5sDh8+HHcKVAW4RyfyAAudyAMFD91FZA6AyQDaVXVs+rFaAI8CaATQCuBmVd1ZvjSpkhw9ehQfffRR6HaWLFniIJsUe/WdUomIk3YA4Pbbbw/dRtB/V5A++v0A7gGQPUfyTADzVXVWer3smQDuKDLHvFpaWox48eLFRrx69WqXb5dYQ4YMiTsFqgIFD91VdSGAHdbDUwB0XsieC+BGx3kRkUOl9tHrVLUtvb0FQF2uF2avsrlt27YS346Iwgh9Mk5TU6DknAZFVWer6jhVHce7r4jiUep19K0iUq+qbSJSD6DdZVIA0L27mdoPfvAD129REeK+ji4iI5A6P1OH1H/os1X1p7EmRUUrdY8+D8C09PY0AMlZvIxc6wDwLVUdA2A8gFtFZEzMOVGRCha6iDwM4HUAp4vIJhGZDmAWgIki0gLgmnRMVUhV21R1SXp7D4BmAMPjzYqKVfDQXVWn5njqase5UMKJSCOA8wC8mf+VlDSJHet+4MCBuFNIhNra2rhTAACISH8AjwP4pqru7uL5GQBmAEC/fv0izo4K4RBYKkhEeiBV5A+p6hNdvSb76grXi0seFjrlJakxn/cBaFbVH8edD5WGhU6FXAbgFgBXiciy9J9JcSdFxUlsH7293fml+Ypgjx84/vjjY8okRVVfBeDuTg6KBffoRB5goRN5gIVO5IHE9tH//M//PO4UYnH33Xcb8XHHHRdTJlRNElvoVLl69OiBhoaG0O1cf/31DrJJGThwoJN2XM6z/8ILL4Ru46mnngr0Oh66E3mAe/SEue6664zY5Rxl5C/u0Yk8wEIn8gALncgDie2jjxgxwojfe++9mDIpry984QtGbP+7iVzgHp3IAyx0Ig+w0Ik8kNg++osvvmjE06ZNM+Lly5cbsYu1vuLw1a9+1Yh79uwZUyZUzbhHJ/IAC53IAyx0Ig8kto9+2mmnGfHrr79uxG+88YYRr1+/3ohvuukmIz506FBm+9xzzzWea21tLTXNon3pS18y4ksvvTSy9yZ/cY9O5AEWOpEHWOhEHkhsH72Q8ePH541tGzduzGxH2Se3ffGLXzTibt34fy2VX8UWOiXX3r17sWjRotDtfPjhhw6ySbn99tudtNPS0uKkHQC49957Q7exffv2QK8LsmzyCBF5WURWisgKEbkt/XitiLwgIi3pvweFzJmIyiTIcWMHgG+p6hgA4wHcKiJjAMwEMF9VRwOYn46JKIGCrI/eBqAtvb1HRJoBDAcwBcCE9MvmAlgA4I6yZOnA3r17Y3nfG264wYgLnUsgKoeizgSJSCOA8wC8CaAu/Z8AAGwBUJfjZ2aISJOING3bti1EqkRUqsCFLiL9kVoj+5uqujv7OVVVANrVz2Wvmz106NBQyVJ8RKRGRJaKyNNx50LFC3TWXUR6IFXkD6nqE+mHt4pIvaqRUTksAAAgAElEQVS2iUg9gEQvfzpoUDznCu2zvX369IklDwduA9AMwM1KCBSpIGfdBcB9AJpV9cdZT80D0HmT+DQAT7pPj5JARBoAXA8g/PUgikWQPfplAG4B8K6ILEs/dieAWQAeE5HpADYAuLk8KVIC/ATAtwEMiDsRKk2Qs+6vAsi1XMjVbtOhpBGRyQDaVfWPIjIhz+tmAJgBAL169YooOwrKm5Fx//AP/xDJ+9h98DPPPDOS9y2jywDcICKTAPQGMFBEHlRVY55qVZ0NYDYADBw4sMsTsxQfDrSmvFT1O6raoKqNAD4H4CW7yCn5WOhEHvDm0J3CU9UFSI2ApArjTaE//vjjkbzPz3/+cyOura2N5H2J8uGhO5EHWOhEHmChE3lAUvejRPRmItuQGkU3BECwqTGiVU15jVTVWO4iyvo955O0zzpp+QDBcgr0e4600DNvKtKkquMif+MCmFd0kvZvSlo+gNuceOhO5AEWOpEH4ir02TG9byHMKzpJ+zclLR/AYU6x9NGJKFo8dCfyQKSFLiLXishqEVkrIrFODy0ic0SkXUSWZz0W61z1Psyhn6TvQDqfLj/zuLmeoy+yQheRGgA/A3AdgDEApqbnh4/L/QCutR6Le676qp5DP4HfASD3Zx63zjn6nIhyj34RgLWqul5VDwF4BKm54WOhqgsB7LAenoLUHPVI/31jxDm1qeqS9PYepH7RnXPox5aXQ4n6DgB5P/PYlGOOvigLfTiA97LiTYj5A+1CoLnqo1DKHPoVINHfAeszj1PnHH1HXTXIk3E55JurvtxKnUOfSpfvM484j8wcfS7bjbLQNwMYkRU3pB9Lkq3pOeoR11z1+ebQjzMvRxL5Hcjxmcelc46+VqS6NleJyINhG42y0BcDGC0io0SkJ1Lzj82L8P2DiHWueg/m0E/cdyDPZx6Lss3Rp6qR/QEwCcAaAOsA3BXle3eRy8NILR55GKm+4nQAg5E6q90C4EUAtRHndDlSh+XvAFiW/jMp7ryq9TuQ7zOPO690bhMAPO2iLY6MI/JAqEP3pA1+IKKulbxHTw9+WANgIlKHvosBTFXVle7SIyIXwswCmxn8AAAi0jn4IWehiwj7CRFS1VxLaZVV37599fjjjw/dzr59+xxkk3Lo0CEn7Rw+fNhJOwDQ0dHhpJ0gv+cwhd7V4IeLQ7RHVeL444/HV77yldDtLF261EE2KRs2FJrZKpitW7c6acd1W4WUfV737MX3iCgeYQo90OAHzVp8j4fuRPEIc9Y9cYMfiKhrJRe6qnYA+DqA55G64+cxVV3hKjFKDl5GrXyh+uiq+gyAZxzlQgmUdQ955jKqiMzjZdTK4s0iiy7V1NQYcZ8+fTLb9mUcV5d1YlT0ZVRKHt6mSoUk+h5yCoaFTk6IyAwRaRKRJpcDXcgNHrp3oWfPnkZ80kknGfHIkSON+JRTTslsDxgwwHjOHkn1yiuvGPHbb79dcp4RKfoy6oknnsjLqAnDPToVwsuoVYB7dMpLVTtEpPMyag2AObyMWnlY6FQQL6NWPhY6gOHDzZPIl1xyiRGPHz/eiO0++6BBH6+nMHDgQOO57t3Nj9hu+5577jHi1157LUDGRMVhH53IAyx0Ig/w0J2cO+6443DdddeFbmfVqlUOskn51Kc+5aQdl12rq666KnQbzz//fKDXeVnoF1xwgRFfccUVRnz22Wcbce/evY3Yvja+Z8+ezHavXr3yvvcJJ5xgxFOmmCsStbW1GfH69evztkcUBA/diTzAQifyAAudyANV20e3byXNPvFhnwQZNmyYEe/cudOIly9fbsRvvmkutpl9E8fgwYPz5nHyyScbcfY1eAAYOnSoEbOPTi5wj07kARY6kQdY6EQeqNo++oUXXmjE2QM4+vfvbzzX2tpqxIsXLzbit956y4h37NiR833ttmz2IJAePXoY8ZEjR/L+PFEpuEcn8gALncgDLHQiD1RNH90en37eeecZ8XvvfTyR6d69e43nVq40Zy62F/ezr4UXw55fzr5Obvf37bHuRC5wj07kARY6kQcq9tDdnlbZHlpqW7duXWbbPlTftWuXEffr18+Ijx49asTnnHOOEZ922mmZ7bq6OuM5e7F7e6qp9vZ2I3799deNePXq1SAKi3t0Ig+w0Ik8UPDQXUTmAJgMoF1Vx6YfqwXwKIBGAK0AblbVnbnaIL/07NnzmKsNpbjzzjsdZJPywx/+0Ek7t99+u5N2AODMM88M3UbQlX6C9NHvB3APgAeyHpsJYL6qzkqvlz0TwB1F5hiKPR2Ufbunfdnq/fffz2x/8MEHeX+2b9++Rmz32c844wwjzu6j231wmz3E1b50N2LECCNmH51cKHjorqoLAdiDu6cAmJvengvgRsd5EZFDpfbR61S1c2THFgB1+V5MRPEKfXlNVVVEcq6eKSIzAMwI+z5EVLpSC32riNSrapuI1ANoz/XC7OV08/2HUIjdd7Wnf7Jv99y/f78Rd+v28cGLPb2z3UcXESMeMmRI3lzs98qWPRU0AHz44YdGbE9blZ0nkSulfqvmAZiW3p4G4Ek36VDSiMgIEXlZRFaKyAoRuS3unKh4BQtdRB4G8DqA00Vkk4hMBzALwEQRaQFwTTqm6tQB4FuqOgbAeAC3isiYmHOiIhU8dFfVqTmeutpxLpRA6ZOubentPSLSDGA4gJV5f5ASpWLGuttLHWVfFweOXSbJvj599dUf/780Zoy5Q7L7+3369DHiLVu2GPHu3buNOPvW04MHDxrP2dfz7Xjr1q1GvH37diSViDQCOA/Am/lfSUnDMz8UiIj0B/A4gG+q6u4unp8hIk0i0mQPSKL4sdCpIBHpgVSRP6SqT3T1GlWdrarjVHWcvYgFxY+FTnlJ6lrjfQCaVfXHcedDpUlsH92+Lr5p0yYjtvu6dr/7r/7qr4x42rRpmW37XnZ7/PmiRYuM2D4Utfvh2dfZ7fvL7XvdP/roo7xtZ095lRCXAbgFwLsisiz92J2q+kyMOVGRElvolAyq+ioAKfhCSjQeuhN5gIVO5IHEHrrb18Xt+MCBA0a8ZMkSI/7rv/5rI86eu83uJ9t98oULFxqxPT308ccfb8QtLS2ZbXs+Onvsuj2HnG3btm15nycqRWILnSrXnj17MH/+/NDtXHPNNQ6ySfnVr37lpJ3/+I//cNIOcOzOqhT79u0L9DoeuhN5oGr26Pb/bLfeeqsRz507N7Pdvbv5z7anWLYv7X3qU58y4sbGRiPevHlzZtvuYvTu3duI7dtSeahOUeAencgDLHQiD7DQiTxQNX10m72M0htvvBH4Z+0pm+0+u322dOPGjTl/1u6j21NL/elPfwqcF1GpuEcn8gALncgDLHQiD1RtHz0Me00se0mmQ4cOGXH2Ek52n9y+nda+bdW+7k5UDtyjE3mAhU7kARY6kQfYRwdw7rnnGrG9bLJ97due/jl7umdVc9Upewmm7HHxRFHhHp3IAyx0Ig+w0Ik84GUfvX///nmft5dzspdF7tmzpxFnXztva2sznrOvo7uYVYSoWF4WOpVXW1sbZs0Kv8DuggULwieTdvPNNztpp7a21kk7APDII4+EbsOeyCSXIMsmd7k+tojUisgLItKS/ntQyJyJqEyC9NFzrY89E8B8VR0NYH46JqIECrI+eq71sacAmJB+2VwACwDcUZYsHbOXSbbHstvTOdvXzevr6404u89uL+9sL4tMFIeizrpb62PXpf8TAIAtAOqcZkZEzgQ+GWevj51aZDNFVVVENMfPzQAwI2yiRFS6QIWeY33srSJSr6ptIlIPoL2rn1XV2QBmp9vp8j+DKGRP8WyvvGKvaGrfamrH9nTR2VNN20Ne7ZVXK5WI1ABoArBZVSfHnQ8VJ8hZ91zrY88D0LkW8TQAT7pPjxLkNgDNcSdBpQnSR+9cH/sqEVmW/jMJwCwAE0WkBcA16ZiqkIg0ALgewL1x50KlCXLWPd/62Fe7TYcS6icAvg1gQK4XZJ+LsWfNpfh5MzIuexVT+5KXHa9atcqI7SWYLrroopw/nz31czUQkckA2lX1jyIyIdfrss/F9OnTJ7ZzMdQ13tRChVwG4AYRaQXwCFJduAfjTYmKxUKnvFT1O6raoKqNAD4H4CVV/ULMaVGRWOhEHvCmjx5Ga2urEWf39wEge/CQfVtqNVHVBUgNdaYKwz06kQdY6EQeYKETeUDs6YnL+mYi2wBsADAEwPbI3ji4asprpKoOLfwy97J+z/kk7bNOWj5AsJwC/Z4jLfTMm4o0qeq4yN+4AOYVnaT9m5KWD+A2Jx66E3mAhU7kgbgKfXZM71sI84pO0v5NScsHcJhTLH10IooWD92JPMBCJ/JApIUuIteKyGoRWSsisc4DLyJzRKRdRJZnPRbrohQ+LJaRpO9AOp8uP/O4iUiNiCwVkaddtBdZoacnF/wZgOsAjAEwNb0QRFzuB3Ct9Vjci1JU9WIZCfwOALk/87g5naMvyj36RQDWqup6VT2E1CQGUyJ8f4OqLgRg32o2BanFKJD++8aIc2pT1SXp7T1I/aI7F8uILS+HEvUdAPJ+5rEpxxx9URb6cADvZcWbEPMH2oXELEpRpYtlJPo7YH3mceqco++oqwZ5Mi4HTV13jOXao71YRlLyqmb5PvOI88jM0eey3SgLfTOAEVlxQ/qxJNmaXowC+RalKKd8i2XEmZcjifwO5PjM41KWOfqiLPTFAEaLyCgR6YnU/GPzInz/IGJdlMKDxTIS9x3I85nHomxz9KlqZH8ATAKwBsA6AHdF+d5d5PIwUqvEHkaqrzgdwGCkzmq3AHgRQG3EOV2O1GH5OwCWpf9Mijuvav0O5PvM484rndsEAE+7aItDYIk8EOrQPWmDH4ioayXv0dODH9YAmIjUoe9iAFNVdaW79IjIhTDTPWcGPwCAiHQOfshZ6IMGDdITTzwxxFtSUO+//z527tyZa828surWrZvW1NSEbsdFG51cLV/tcl25AQNyLmUX2N69e3HgwIGCv+cwhd7V4IeL8/3AiSeeiF/96lch3pKC+vznPx/be9fU1GDIkCGh2znuuOMcZJOyevVqJ+0MGzbMSTsAcNVVV4Vu43e/+12g15X98pqIzBCRJhFp2rlzZ7nfjoi6EKbQAw1+UNXZqjpOVccNGlSxN10RVbQwhZ64wQ9E1LWSC11VOwB8HcDzSN3x85iqrnCVGCUHL6NWvlCLLKrqMwCecZQLJVDWPeSZy6giMo+XUSsLV1MF0K2beWBjn0tYsGCBEf/nf/6nEV9wwQWZ7UOHDhnPjRtnzr//N3/zN0Z8zz33GHFjY6MRjxgxAjEr+jIqJQ9vU6VCEn0POQXDPTo5ISIzAMwAjj1Covh5U+ipuxFT7IEYb7/9thGfffbZRbX91ltv5XzuvvvuM+I33njDiL/2ta8Z8RNPmLdDxznwJS3wZVSkFxzo0aMH75RKGP7XS4XwMmoV8GaPTqVR1Q4R6byMWgNgDi+jVh4WOhXEy6iVr2oLPbtPDgB1dR9PnPqNb3zDeO6xxx6LJCcAmDt3rhG/+OKLRnzGGWcY8XXXXZfZ5hBiKhX76EQeYKETeaBqD90pPqeddhoeffTR0O289NJLDrJJ+bd/+zcn7Rw+fNhJOwDwpS99KXQbb74ZbK2Jqil0e+aPgQMHGvHIkSMz265mG3Hh3HPPNeJNmzYZcffuVfMrohjx0J3IAyx0Ig+w0Ik8ULEdQPs6ud0nT8DtnYHYk/uNHTvWiHfv/ni9PxezhpKfuEcn8gALncgDLHQiD1RsH92+bp49JryS2GPbjx49asQc304ucI9O5AEWOpEHWOhEHqiYPnqfPn2MuLm52YiXL18eZTrOrFq1Ku/zGzZsyGx/4hOfKHc6VKW4RyfyAAudyAOJPXSvqakx4h07dhjxjTfeGGU6sdm+fXvcKVAV4B6dyAMsdCIPFDx0F5E5ACYDaFfVsenHagE8CqARQCuAm1V1Z/nSpErS0tKCSZMmhW5nypQpDrJJ+eUvf+mknR/84AdO2gGAefPCr4Oxa9euQK8L0ke/H8A9AB7IemwmgPmqOiu9XvZMAHcUmWNe9hBXe+kiX5x11llxp0BVoOChu6ouBLDDengKgM4JyucC8OPMGFGFKrWPXqeqbentLQDq8r2YiOIV+mScqiqAnKtnisgMEWkSkaadO9mNJ4pDqdfRt4pIvaq2iUg9gPZcL8xeTvfMM88MvJzukiVLjHjZsmUlplrZPvjgg8z28ccfH2MmVMlK3aPPAzAtvT0NwJNu0qGkEZERIvKyiKwUkRUiclvcOVHxCha6iDwM4HUAp4vIJhGZDmAWgIki0gLgmnRM1akDwLdUdQyA8QBuFZExMedERSp46K6qU3M8dbXjXCiB0idd29Lbe0SkGcBwACtjTYyKktix7u+++27cKSTCsGHD4k4hQ0QaAZwH4JgFv0RkBoAZwLH3KVD8OASWAhGR/gAeB/BNVd1tP6+qs1V1nKqO69aNX6uk4W+EChKRHkgV+UOq+kTc+VDxWOiUl6SWxLkPQLOq/jjufKg0ie2jHzhwIO4UYmFP/5x900JMSzJdBuAWAO+KSOdghjtV9Zk4kqHSJLbQKRlU9VUAUvCFlGg8dCfyAAudyAOJPXS354S7++67Y8okWp/85CeN+MQTT4wpE6omiS10qly1tbWYOjXXgMrgtm7d6iCblO9973tO2lm6dKmTdgBg5crwgwvtSVNz4aE7kQcSu0c/4YQT4k4hFuPHjzdiDiclF7hHJ/IAC53IAyx0Ig8kto++evVqI77uuuuM+Nlnn40ynbL527/9WyM+9dRTY8qEqhn36EQeYKETeYCFTuSBxPbR7SmU7LW83n77bSN+//33y55TOezbt8+IY7oVlaoc9+hEHmChE3mAhU7kgcT20Xv37m3EV1xxhRGff/75Rrxq1SojXrRokRFn3+Xzm9/8xkWKJfnKV76SNyYqB+7RiTzAQifyAAudyAOJ7aMX0q9fPyO+4IIL8sbZa7PH2Ue38+7Zs2dMmZBPKrbQKbn27t2Lt956K3Q7L7/8soNsUq655hon7YwcOdJJOwDwne98J3Qb3/3udwO9LsiyyV2ujy0itSLygoi0pP8eFDJnIiqTIH30XOtjzwQwX1VHA5ifjokogYKsj55rfewpACakXzYXwAIAd5QlSwfssfFRufLKK43405/+dCx5kN+KOuturY9dl/5PAAC2AKhzmhkRORO40POtj62qCkBz/NwMEWkSkabsM99UWUSkRkSWisjTcedCxQt01j3H+thbRaReVdtEpB5Ae1c/q6qzAcwGgDPPPLPL/wyi0NzcHMv7fvaznzXiwYMHx5KHA7cBaAYwMO5EqHhBzrrnWh97HoBp6e1pAJ50nx4lgYg0ALgewL1x50KlCbJH73J9bACzADwmItMBbABwc3lSpAT4CYBvA+CsGBUqyFn3fOtjX+02HUoaEZkMoF1V/ygiE/K8bgaAGQDQq1eviLKjoLwZGXfJJZdktn/xi1+U7X3sVWDr6+vL9l4RuQzADSIyCUBvAANF5EFV/UL2i7LPxQwYMCC2czHUNd7UQnmp6ndUtUFVGwF8DsBLdpFT8rHQiTzgzaE7haeqC5AaAUkVxptCnzBhQiTvc+TIESPmEkuUBDx0J/IAC53IAyx0Ig9I6n6UiN5MZBtSo+iGANge2RsHV015jVTVoeVIppCs33M+Sfusk5YPECynQL/nSAs986YiTao6LvI3LoB5RSdp/6ak5QO4zYmH7kQeYKETeSCuQp8d0/sWwryik7R/U9LyARzmFEsfnYiixUN3Ig9EWugicq2IrBaRtSIS6/TQIjJHRNpFZHnWY7HOVe/DHPpJ+g6k8+nyM4+b6zn6Iit0EakB8DMA1wEYA2Bqen74uNwP4Frrsbjnqq/qOfQT+B0Acn/mceuco8+JKPfoFwFYq6rrVfUQgEeQmhs+Fqq6EMAO6+EpSM1Rj/TfNyJCqtqmqkvS23uQ+kV3zqEfW14OJeo7AOT9zGNTjjn6oiz04QDey4o3IeYPtAuJmau+SufQT/R3wPrM49Q5R99RVw3yZFwO+eaqL7dS59Cn0uX7zCPOIzNHn8t2oyz0zQBGZMUN6ceSZGt6jnrkm6u+nPLNoR9nXo4k8juQ4zOPS+ccfa1IdW2uEpEHwzYaZaEvBjBaREaJSE+k5h+bF+H7BxHrXPUezKGfuO9Ans88FmWbo09VI/sDYBKANQDWAbgryvfuIpeHkVo88jBSfcXpAAYjdVa7BcCLAGojzulypA7L3wGwLP1nUtx5Vet3IN9nHnde6dwmAHjaRVscGUfkgVCH7kkb/EBEXSt5j54e/LAGwESkDn0XA5iqqivdpUdELoSZBTYz+AEARKRz8EPOQhcR9hMipKq5ltIqq4EDB+rQoeEnt+nZs6eDbFJqamqctHPw4EEn7QDA2rVrnbQT5PccptC7GvxwcYj2qEoMHToU3//+90O3c/LJJzvIJqVfv35O2lm3bp2TdgDgM5/5TOg2Ojo6Ar2u7PO6Zy++R0TxCFPogQY/aNbiezx0J4pHmLPuiRv8QERdK3mPrqodIvJ1AM8DqAEwR1VXOMuMiJwJdR1dVZ9R1dNU9RRV/VdXSVGycLxE5ePda5RXQieLoCJ5s5pqVAYOHGjEY8aYNTFs2DAjfv/99424qampPImVrujxEpQ83KNTIYEmixCRGSLSJCJNu3fHdjs35cBCJydUdbaqjlPVcfZRDcWPh+6O2Xuzjz76yIjPOeccIx41apQR79q1y4hdDZMMIZGTRVBxuEenQjheogpwj055cbxEdWChU0Gq+gyAZ+LOg0rHQi+z5cuXG/HGjRuN+NZbbzXi0aNHG3EC+uhUBdhHJ/IAC53IAzx0J+eOHj2K/fv3h26nd+/eDrJJ+fnPf+6knVdeecVJOwDQ3Bx+abWbbrop0OtY6CXo1auXEXfv/vHHuHfv3rw/a19nX7x4sRFv3749ZHZEx+KhO5EHWOhEHmChE3mAffQA7GmHb7zRXJ78hBNOyGz36NHDeO7Xv/61Ee/bt8+I7Vk8P/jgg5LzJMqFe3QiD7DQiTzAQifyAPvoXbCne5o4caIRjxgxwoizr6Nv2rTJeK6hocGIzzrrLCO+4YYbjPjxxx834nvvvTdAxkT5cY9O5AEWOpEHWOhEHmAfHcDll19uxGeccYYRF5rXbc6cOZnt9vb2vO9l329eV1dnxCeeeKIRi3y8Im6pa9kTcY9O5AEWOpEHvDx0tw/V/+Iv/sKITznlFCN+7bXXjPiBBx4w4kKH6/l+1j6U37JlixHzcJ1c4B6dyAMsdCIPFDx0F5E5ACYDaFfVsenHagE8CqARQCuAm1V1Z/nSpEpy4MABrF69OnQ7TzzxhINsUp577jkn7Xz5y1920g4ALFq0KHQb9kpAuQTpo98P4B4A2Z3LmQDmq+qs9HrZMwHcUWSOsfnkJz9pxJdccokRP/nkk0Z89913G/GhQ4dKfu/GxkYjHj7cXK/QxTxiRLaCh+6quhDADuvhKQDmprfnArgRRJRYpZ51r1PVtvT2FgB1uV4oIjMAzCjxfYjIgdCX11RVRSTnNSBVnQ1gNgDkex0RlU+phb5VROpVtU1E6gEEv5Ack5NPPjmzbfeTX3/9dSO2bxUN0ycfPHiwEd91111GbN+26vIElAsiMgKp8zN1ABTAbFX9abxZUbFKvbw2D8C09PY0AE/meS1Vtg4A31LVMQDGA7hVRMbEnBMVqWChi8jDAF4HcLqIbBKR6QBmAZgoIi0ArknHVIVUtU1Vl6S39wBoBjA8/09R0hQ8dFfVqTmeutpxLpRwItII4DwAb8abCRXLm7HuF1xwQWZ7xw7zauGLL75oxPZtqGF85jOfMeIrr7zSiO0lmDZv3uzsvV0Skf4AHgfwTVXd3cXzmasrAwcOjDg7KoRDYKkgEemBVJE/pKpdni1U1dmqOk5Vx/Xt2zfaBKkgFjrlJamZL+4D0KyqP447HyoNC50KuQzALQCuEpFl6T+T4k6KipPYPnpNTY0RHzlyJFR7R48ezWyvWrXKeM7usxdzf7ntuOOOM2K7T27f675kyRIj3rp1a8nvXQ6q+ioAKfhCSjTu0Yk8wEIn8gALncgDie2jZ/epXVi7dm1me8OGDcZzLq+bX3rppUacff0eAFpbW434N7/5jRHbc8YRuZDYQqfKNWDAAEyYMCF0O/aJyzBczOYCAP/1X//lpB0A6N27d+g29u3bF+h1PHQn8kBi9+iFpjnu2bOnEV944YV5X9/W1pbZHjJkiPFc9mqoALB3714j7tevnxHbl/pOO+20zPakSeYlZnuqqJdfftmIly5dasSHDx8+JneisLhHJ/IAC53IAyx0Ig8kto9eSI8ePYzY7lfbK6JmT9mUvUIpcGw/uX///kb8hz/8wYgPHjxoxNmX5+wlluzX2md/wwy3JQqKe3QiD7DQiTzAQifyQMX20e0++bJly4x427ZtRjxixIjM9oABA4zn6uvrjdgellrIqFGjMttnnnmm8VxTU5MRv/TSS0Zs3yJLVA7coxN5gIVO5AEWOpEHKraPXog9bXI5p1G+/fbbM9t9+vQxnrP75Nm3yxJFhXt0Ig+w0Ik8wEIn8kDV9tHLafLk/9/evQdZUd15AP/+GF7yGN6OIyDjAyUjGh+IbPCB4gPRCLF2FRJZUkWFWstsmVR2FaPrbtUmWWt3Y5mU7mZZRcliUCtaCyKaIIKIqygqIDDAAIKAAyOCPASZGee3f9yea5/DffS93be77+3vp4qif7fv9P3Rcw/dp/v079xixOPHfzMN3fr164119tj2IMtWEXnFhk6Bq66uxo033uh7O/bDRn4EVZZq8uTJgWwHAF5++WXf2zh06JCn93mZNnmoiCwTkY0iskFE7nFe7y8iS0Sk0fm7n8+ciahEvPTR2wD8TCgnyu4AACAASURBVFXrAYwBcLeI1AOYBWCpqg4HsNSJiSiGvMyP3gSgyVk+IiINAAYDmARgnPO2uQCWA7ivJFnGzPe//30jdp8+/eEPfzDWbdiwIZSciHIpqI8uInUALgawCkCN858AAOwFUJPlZ9LzZhNRNDzfXhORXkjNkf0TVT3sXqepkq0Zy7a65832lSlFSkSqRORDEVkUdS5UOE9HdBHpglQjf0ZVX3Re3icitaraJCK1ACq2JpI9rHXAgAFG7C41tWLFCmOd16uiZeAeAA0AqqNOhArn5aq7AHgSQIOqPuJatRDAdGd5OoAFwadHcSAiQwDcDOCJqHOh4ng5dR8LYBqAa0VkjfNnIoCHAVwvIo0ArnNiqkyPArgXQNYJ8URkpoisFpHVdtEPip6Xq+4rAUiW1eOzvE4VQkRuAdCsqu+LyLhs71PV2QBmA8CoUaNyT7NDoUvMyDj3FE4tLS0F/WxNjXlDwZ6N1R1/8sknRWQXa2MB3OqcxXUHUC0i81T1zojzogLwoRbKSVXvV9UhqloHYAqA19nIyw8bOlECJObUnfxT1eVIjYCkMpOYhl5ov9ztu9/9rhHbJZrfeeed9PLevXuL/hyiUuGpO1ECsKETJQAbOlECSOp5lJA+TOQzADsBDASwP7QP9q6S8hqmqoNKkUw+rt9zLnHb13HLB/CWk6ffc6gNPf2hIqvj+DQb8wpP3P5NccsHCDYnnroTJQAbOlECRNXQZ0f0ufkwr/DE7d8Ut3yAAHOKpI9OROHiqTtRAoTa0EVkgohsFpGtIhJpeWgRmSMizSKy3vVapLXqk1BDP07fASefjPs8akHX6AutoYtIFYDHAdwEoB7AVKc+fFSeBjDBei3qWvUVXUM/ht8BIPs+j1pHjb5AhHlEHw1gq6puV9UWAM8iVRs+Eqq6AsAB6+VJSNWoh/N3cPPveMupSVU/cJaPIPWL7qihH1leAYrVdwDIuc8jU4oafWE29MEAdrni3Yh4h2bgqVZ9GIqpoV8GYv0dsPZ5lPLW6CsUL8ZlkatWfakVW0Ofipdrn4ecR7pGX5DbDbOh7wEw1BUPcV6Lk31OjXpEVas+Vw39KPMKSCy/A1n2eVQ6avTtQKprc62IzPO70TAb+nsAhovImSLSFan6YwtD/HwvIq1Vn4Aa+rH7DuTY55EoWY0+VQ3tD4CJALYA2AbggTA/O0Mu85GaPLIVqb7iDAADkLqq3QjgNQD9Q87pCqROy9cBWOP8mRh1XpX6Hci1z6POy8ltHIBFQWyLI+OIEsDXqXvcBj8QUWZFH9GdwQ9bAFyP1KnvewCmqurG4NIjoiD4qQKbHvwAACLSMfgha0MXEfYTQqSq2abSKqnOnTtrt27dfG+nf//+AWST0qdPn0C2E8S/q8PatWt9b6O9vR3t7e15f89+GnqmwQ+X+9geVYhu3bphxIgRvrczbdq0ALJJufHGGwPZzjnnnBPIdoCTp/oqxuHD3m75l7yuu4jMBDCz1J9DRNn5aeieBj+oa5ZNnroTRcPPVffYDX4gosyKbuiq2gbgxwD+hNQTP8+r6oagEqP44G3U8uerj66qiwEsDigXiiHXM+Tp26gispC3UcsLn16jfGL3DDkVjg2d8on1M+TkTWKmTabSct9G7dq1a8TZkI0N3YPTTjvNiLt06WLEn3/+eXr52LFjoeQUooJvo/bs2ZO3UWOGp+6UD2+jVgAe0SknVW0TkY7bqFUA5vA2avlhQ6e8eBu1/LGh4+Q+uP2kU+fO5m764osvjLgC++VUYdhHJ0oANnSiBOCpOwWutrYWDz30kO/tPPDAAwFkk3LRRRcFsp1vfetbgWwHAO6++27f23jyySc9vS+RDd0uHnDqqacacUtLixF/9tlnRmxXGbn66qvTy5dccomxbs8e85bz888/X1iyRAHgqTtRArChEyUAGzpRAlRsH91+sKK+/psprwcPNh++OnHihBFv3Lgx53r3tgDgiiuuSC9PmmQ+wfn+++ZceeyjUxR4RCdKADZ0ogRgQydKgIrto9v96Kuuuiq9bN/b3rx5sxGffvrpRty9e/ec691F9BsaGnK+t1Mn8//W9vb2k3InChqP6EQJwIZOlABs6EQJUDF9dPuZ8ssvN+d7dPeFP/74Y2NddXW1Edt9crsfvW/fPiM+ePBgermtrc1YZz8EwT45RYFHdKIEYEMnSoCyPXXv0aOHEdvPGw8ZMsSI9+7dm16255Tu1auXEYuY88ofPXrUiFtbW434q6++Si/bpaA//PDDk3InChuP6EQJwIZOlAB5T91FZA6AWwA0q+pI57X+AJ4DUAdgB4DbVfVgtm1QsnTq1OmkOxfF2LAhuPLxv/3tbwPZTm1tbSDbAYBDhw753sbXX3/t6X1e+uhPA3gMwO9dr80CsFRVH3bmy54F4L4Cc/TFvm1lP3pq74AdO3akl/OVaz7jjDOM2C737O6TA8DQod/MWDRw4EBj3f79++3UiUKX99RdVVcAOGC9PAnAXGd5LoDJAedFRAEqto9eo6pNzvJeADUB5UNEJeD79pqqqohknT3TPZ0uEUWj2Ia+T0RqVbVJRGoBNGd7o3s63Vz/IeTTv39/I7700kuNePjw4Ua8adMmM2HXsFX7vrk9LPXAAbOncuTIESMeMGCAEbv7/Oedd56xzi4tvWzZMhCFrdhT94UApjvL0wEsCCYdihsRGSoiy0Rko4hsEJF7os6JCpe3oYvIfABvAzhPRHaLyAwADwO4XkQaAVznxFSZ2gD8TFXrAYwBcLeI1Of5GYqZvKfuqjo1y6rxAedCMeRcdG1ylo+ISAOAwQA25vxBipWyGetuT5tk933r6uqM2J5Gyd2Ht8eu55sW2R6/bo+zHz16dHr5zDPPNNZ9+umnqBQiUgfgYgCros2ECsUhsOSJiPQC8AKAn6jq4QzrZ4rIahFZHcSILwoWGzrlJSJdkGrkz6jqi5neo6qzVXWUqo7q06dPuAlSXmzolJOkntl9EkCDqj4SdT5UnLLpo9tTLNn3zc8++2wjth+qeOONN9LLn3zyibHOXQoKOPl59XPPPdeIp02bZsQ33nhjennNmjXGugULyv7O41gA0wB8JCId/7ifq+riCHOiApVNQ6doqOpKAJL3jRRrPHUnSgA2dKIEKJtTd7uM8vHjx43YfkZ82LBhRuy+v23/rD0l07e//W0jvuaaa4z4jjvuMOKWlpb08ttvv22se/fdd0EUtbJp6FQ+du/ejVmzZvnejj0oyo+77747kO3YF279uPrqq31v4+WXX/b0Pp66EyVA2RzRd+3aZcTr1q0z4lNOOcWId+/ebcTuoaj2kFb3TKvAycNpR44cacT2zC7z5s1LL7/55pvGOrtLQRQFHtGJEoANnSgB2NCJEqBs+uh2OSe7JJNd3rlbt25G7O4r21MqqZoVruwpmewrrUuWLDHiP/zhD+lle6ZWojjgEZ0oAdjQiRKADZ0oAcqmj25btcqsZmT3jc866ywjdg9Ttcs5X3bZZUbcqZP5/59dWsp+FNX92Ovnn3+eK22iSPCITpQAbOhECcCGTpQAZdtHtzU3N+eMc7GnaLKnZLbX792714hPnDjh+bOIosAjOlECsKETJQAbOlECVEwfvRD2FEz2NEr2fXX7WfimpiYj3rp1a4DZEQUvkQ2dSuvEiROB/Odnz5Hnh10QpFgXXHBBINsBgGeffdb3NryWtvIybXLG+bFFpL+ILBGRRufvfj5zJqIS8dJHzzY/9iwAS1V1OIClTkxEMeRlfvRs82NPAjDOedtcAMsB3FeSLANWU1NjxOeff74R29M/bdxoTgVuT8lMFHcFXXW35seucf4TAIC9AGqy/BgRRcxzQ881P7amSrRolp9Lz5vtK1OKlIhUiciHIrIo6lyocJ6uumeZH3ufiNSqapOI1ALIOOZUVWcDmO1sJ+N/BmHr18+8bmgPef3yyy+N2C5TtWfPntIkFm/3AGgAUJ3vjRQ/Xq66Z5sfeyGA6c7ydABlPz8wZSYiQwDcDOCJqHOh4ng5omecHxvAwwCeF5EZAHYCuL00KVIMPArgXgC9o06EiuPlqnuu+bHHB5sOxY2I3AKgWVXfF5FxOd43E8BMZzmk7MirRI6Ms2dmtfvkx44dM2J7Cqe+ffsasV2aqsKMBXCriEwE0B1AtYjMU9U73W9yX4upqqqKxbUY+gYfaqGcVPV+VR2iqnUApgB43W7kFH9s6EQJkMhTdyqOqi5HagQklZlENnR7CGtjY6MR2+Wet2/fbsQsHUXlhqfuRAnAhk6UAGzoRAkg9pTBJf0wkc+QGkU3EMD+0D7Yu0rKa5iqDipFMvm4fs+5xG1fxy0fwFtOnn7PoTb09IeKrFbVUaF/cB7MKzxx+zfFLR8g2Jx46k6UAGzoRAkQVUOfHdHn5sO8whO3f1Pc8gECzCmSPjoRhYun7kQJwIZOlAChNnQRmSAim0Vkq4hEWgdeROaISLOIrHe9FumkFEmYLCNO3wEnn4z7PGpBF+MMraGLSBWAxwHcBKAewFRnIoioPA1ggvVa1JNSVPRkGTH8DgDZ93nUOopxBiLMI/poAFtVdbuqtgB4FqlJICKhqisA2KVhJiE1GQWcvyeHnFOTqn7gLB9B6hfdMVlGZHkFKFbfASDnPo9MKYpxhtnQBwNwT0u6GxHv0AxiMylFhU6WEevvgLXPo9RRjLM9qA3yYlwWuSalKLViJ8ug4uXa5yHnkS7GGeR2w2zoewAMdcVDnNfiZJ8zGQVyTUpRSrkmy4gyr4DE8juQZZ9HpaMY5w6kujbXisg8vxsNs6G/B2C4iJwpIl2RKjS4MMTP9yLSSSkSMFlG7L4DOfZ5JEpWjFNVQ/sDYCKALQC2AXggzM/OkMt8pGaJbUWqrzgDwACkrmo3AngNQP+Qc7oCqdPydQDWOH8mRp1XpX4Hcu3zqPNychsHYFEQ2+IQWKIE8HXqHrfBD0SUWdFHdGfwwxYA1yN16vsegKmqujG49IgoCH7KPacHPwCAiHQMfsja0KuqqtSe3ohKo7W1FV9//XUkk6B169ZNe/To4Xs7AwYMCCCblCNHjgSync6dg6uQ3t7u/zb5oUOHcOzYsby/Zz9ZZxr8cLn9Jvfke507d8awYcN8fCR5tXNnvpJtpdOjRw+MH+9//s1p06YFkE3KsmXLAtlOkP/5HD9+3Pc2nnrqKU/vK/ntNVWdraqjVHVUVVVVqT+OiDLw09BjOfiBiE7mp6HHbvADEWVWdENX1TYAPwbwJ6Se+HleVTcElRjFB2+jlj9flxBVdTGAxQHlQjHkeoY8fRtVRBbyNmp5SeRsqjb7lt+FF15oxOPGjTNie+xBQ8M39QH+93//11iX7+q3fRW3b9++RhyDC5gF30al+OFjqpRPrJ8hJ294RKdAuMdLnHLKKRFnQ7bENPROnb45eamrqzPWjRkzxoirq6uN+P33zRoA9un4nj17sq7L5/PPPzdiu1swcODAgrZXAp5uo6rqbDgTDvTr149PSsUMT90pH95GrQCJOaJTcVS1TUQ6bqNWAZjD26jlhw2d8uJt1PJXsQ3d3ScHgEsvvTS9fOWVVxrrDhwwqz4fPmzWBrRveX3xxRdG7O5Ht7W1Ges2bdrkMePMufTv3z+9bP+biLziN4coAdjQiRKgYk/dKTqHDx/Gn//8Z9/beeGFFwLIJmXUqFGBbKdfv+Cmvbv//vt9b8PrPqqYhm4P0rj66quN+KKLLkov2/eue/XqZcTbtm0z4t///vdGfPDgwaLzLFRra2t6uVu3bqF9LlUWnroTJQAbOlECsKETJUDZ9tHte8rXXnutEV9yySVGfPTo0fTyOeecY6xbuXKlEf/mN78JIkWi2OARnSgB2NCJEoANnSgByraPbpdgsp/bPuOMM4zYfa98/vz5xrpf//rXgeV13XXXGfFrr73ma3stLS3pZd5Hp2LxiE6UAGzoRAnAhk6UAGXTR7cfJrjhhhuMeMqUKUbs7tsCwFtvvZVe/vd///dAc7v55pvTy+7n3gHgnXfeMWL3/Xwv7OfbiYrBIzpRArChEyVAbE/d7dlTRo4cacTDhw83YntGk9WrVxvxT3/608By+973vmfE7nLRdl6DB5tzHWzevLmgzxLJO8c9UV48ohMlABs6UQLkPXUXkTkAbgHQrKojndf6A3gOQB2AHQBuV9Xwyq5QrPXq1Qvf+c53fG+nubk5gGxSHn/88UC2U2jXKxf7Dk0xevTo4el9XvroTwN4DIC7ntIsAEtV9WFnvuxZAO4rMMecTj/9dCN2l4ICTt5J7e3tRmw/enrkyJGic7nmmmuMeNiwYUb8rW99K728atUqY53fL4Z9m5CoGHlP3VV1BYAD1suTAMx1lucCmBxwXkQUoGL76DWq2uQs7wVQE1A+RFQCvm+vqaqKSNbZM93T6XbuHNu7eUQVrdiWt09EalW1SURqAWS9auKeTrd79+6ep9N1T0UEnFwaaujQoUb8yiuvGPF//dd/ef2ok9hlquzrA5dddpkRb9myJb38y1/+sujP9ZILUTGK/RYtBDDdWZ4OYEEw6VDciMhQEVkmIhtFZIOI3BN1TlS4vA1dROYDeBvAeSKyW0RmAHgYwPUi0gjgOiemytQG4GeqWg9gDIC7RaQ+4pyoQHlP3VV1apZV4wPOhWLIueja5CwfEZEGAIMBbIw0MSpIbK+O1dSYF/Ld96qBk6dgClJ9fe4DlvuRVwB45plnSpaLPeY/SiJSB+BiAKsyrEtfdO3evXuoeVF+vNJDnohILwAvAPiJqh6216vqbFUdpaqjunbtGn6ClBMbOuUlIl2QauTPqOqLUedDhWNDp5wk9ZzskwAaVPWRqPOh4sS2j37s2DEjfvfdd4147NixRmw/f+7H+vXrjdh+1v3TTz814i+++CKwz7aV8lqER2MBTAPwkYiscV77uaoujjAnKlBsGzrFg6quBMDqF2WOp+5ECcCGTpQAsT11t+8f2/3mjz76yIgbGhpKlsvatWtLtu18eKuKghDbhk7lq7W19aQLlsUI8j+5Dz/8MJDtLFgQ3GMd9sCrYuzevdvT+3jqTpQAsT2ib9++3YjtmUTtMsh9+vQx4t69exuxn1JSYbJLaBEFgUd0ogRgQydKADZ0ogSIbR/dvpp44sQJI7aHpdqzjtrvL4R7iiXg5Omg7FLSmzZtKvqzbF7rdBMVgkd0ogRgQydKADZ0ogSIbR+9tbXViJuamozYLldkD5m1y0G5R2rZ96rvvfdeI/7ud79rxB988IERP/HEE9nSLtigQYOMmOWdqRT4rSJKADZ0ogRgQydKgNj20W2q5mxOx48fN+Kvvvoq58+PGDEivXzHHXcY62677TYjbmxsNOJ58+Z5zrNQ/fr1K9m2iTrwiE6UAGzoRAnAhk6UAGXTR8/H7sPbqqur08v2lMv2PXu71PR///d/+8zuG+yTUxQqpqFTfPTs2ROjR4/2vZ1du3YFkE3Kb3/720C2s2jRokC2AwBnnnmm7214nc/Ay7TJGefHFpH+IrJERBqdv3moIoopL330bPNjzwKwVFWHA1jqxEQUQ17mR882P/YkAOOct80FsBzAfSXJMgBDhgxJL48aNcpYZ4+bf/XVV0uWx4ABA0q2baJsCrrqbs2PXeP8JwAAewHUZPkxIoqY54aea35sTV3yznjZW0RmishqEVn99ddf+0qWoiMiVSLyoYgEdzWKQuPpqnuW+bH3iUitqjaJSC2A5kw/q6qzAcwGgO7du+e+B1ZC7lto27ZtM9bZj8D+6U9/Cuxz3bf1gLJ+DPUeAA0AqvO9keLHy1X3bPNjLwQw3VmeDiC4KSwoVkRkCICbAQT3ID6FyssRPeP82AAeBvC8iMwAsBPA7aVJkWLgUQD3Auid740UT16uuueaH3t8sOlQ3IjILQCaVfV9ERmX430zAcwEgF69eoWUHXmVmJFx7gn73nnnHWOd3W/esGFDYJ87cODAwLYVkbEAbhWRiQC6A6gWkXmqeqf7Te5rMYMGDYrsWgxlVrZXhigcqnq/qg5R1ToAUwC8bjdyij82dKIESMypO/mnqsuRGgFJZSYxDf3AgQPp5Z49exrr9uzZY8SHDh0q+nPc1wIAoHPnxOxiijGeuhMlABs6UQKwoRMlgOQrwRToh4l8htQouoEA9of2wd5VUl7DVHVQ/rcFz/V7ziVu+zpu+QDecvL0ew61oac/VGS1qo7K/85wMa/wxO3fFLd8gGBz4qk7UQKwoRMlQFQNfXZEn5sP8wpP3P5NccsHCDCnSProRBQunroTJUCoDV1EJojIZhHZKiKRlocWkTki0iwi612vRVqrPgk19OP0HXDyybjPoxZ0jb7QGrqIVAF4HMBNAOoBTHXqw0flaQATrNeirlVf0TX0Y/gdALLv86h11OgLRJhH9NEAtqrqdlVtAfAsUrXhI6GqKwAcsF6ehFSNejh/Tw45pyZV/cBZPoLUL7qjhn5keQUoVt8BIOc+j0wpavSF2dAHA3BPprUbEe/QDGJTq75Ca+jH+jtg7fModdToaw9qg7wYl0WuWvWlVmwNfSpern0ech7pGn1BbjfMhr4HgHu+4iHOa3Gyz6lRj1y16kspVw39KPMKSCy/A1n2eVQ6avTtQKprc62IzPO70TAb+nsAhovImSLSFan6YwtD/HwvIq1Vn4Aa+rH7DuTY55EoWY0+VQ3tD4CJALYA2AbggTA/O0Mu85GaPLIVqb7iDAADkLqq3QjgNQD9Q87pCqROy9cBWOP8mRh1XpX6Hci1z6POy8ltHIBFQWyLI+OIEsDXqXvcBj8QUWZFH9GdwQ9bAFyP1KnvewCmqurG4NIjoiD4KVGaHvwAACLSMfgha0MXEfYTQqSq2abSKqmePXtq3759fW/n+PHjAWSTcvDgwUC207t3cNPPBbGPDhw4gKNHj+b9Pftp6JkGP1zuY3tUIfr27Yu/+Zu/8b2ddevWBZBNyh//+MdAtjN69OhAtgMAkyb5HxT4b//2b57eV/Ki4+7J94goGn4auqfBD+qafI+n7kTR8HPVPXaDH4gos6KP6KraJiI/BvAnAFUA5qhqcPMNE1FgfN1HV9XFqnquqp6tqr8MKimKF46XKH98eo1yimmxCCoQp/oswumnn27E7nurJ06cMNbt2LEjjJRKqeDxEhQ/PKJTPp6KRYjITBFZLSKrv/zyy9CSI2/Y0CkQqjpbVUep6ih7/nmKHk/dMxg5cqQR33HHHUZ81llnGbF7KOPOnebcgm+88YYRP/fcc0GkGKZYFougwvCITvlwvEQF4BGdcuJ4icrAhk55qepiAIujzoOKx4YO4K677jLia665xojtPnmXLl2M2N0vP/vss411Q4cONeIDB8xS8kuWLCksWaIisI9OlABs6EQJwFN3Clz37t1x3nnn+d6OfavSj3HjxgWynb/9278NZDsAcO+99/reRnOztxL/iWno7r7y3//93xvrRowYYcS1tbVGbFc6+fOf/2zE/fv3Ty/fcMMNxrpPP/3UiM844wwjPuecc4x469atJ+VO5BdP3YkSgA2dKAHY0IkSoGL76BdeeKERP/jgg+nlAQMGGOuGDRtmxAsXmiM8H3/8cSPetm1b1s/9j//4DyM+9dRTjfjwYXOizl69ehmxfY++tbU162cRecUjOlECsKETJQAbOlECVEwfvUePHkb8wx/+0Ijd/XB77Prvfvc7I7Znv7D71bnYc9nZffRdu3YZ8aFDhzxvm6hYPKITJQAbOlECsKETJUDF9NH/6q/+yoiHDx9uxO7x6P/5n/9prPvHf/xHIy50zvgxY8akl2+77TZjnT123R43z/vkFAYe0YkSgA2dKAHK9tTdfboMAFdffbURX3rppUa8ePE3Jc8eeughX589depUI542bVp62a5pPmjQICN+/fXXjZiPpVIYeEQnSoC8DV1E5ohIs4isd73WX0SWiEij83e/0qZJRH54OXV/GsBjAH7vem0WgKWq+rAzje4sAPcFnx6Vo86dO2PgwIG+txPkqMGgSkm99dZbgWwHAH7605/63sa//Mu/eHpf3oauqitEpM56eRKAcc7yXADLUeKGbg9xnTx5shFfcsklRrx//34j/sUvfuH5s7p27WrEP//5z4348ssvN2IRSS/bw2v37DFnL7Jvp9mf1dbWZsTt7e0eMibKrdg+eo2qNjnLewHUBJQPEZWA76vuqqoiknWEiYjMBDDT7+cQUfGKPaLvE5FaAHD+zlpz1j2dbpGfRUQ+FXtEXwhgOoCHnb8XBJZRFqNHjzZiu2yyPRXSL3/5SyP+7LPP0sv9+pk3CcaPH2/EU6ZMMeLq6uqc8eDBg9PL9iOtr7zyihHnq1Vul5Y6evRozveXmogMRepCbA0ABTBbVX8TaVJUMC+31+YDeBvAeSKyW0RmINXArxeRRgDXOTFVpjYAP1PVegBjANwtIvUR50QF8nLVfWqWVeOzvE4VxLno2uQsHxGRBgCDAWyMNDEqCEfGkWfObdaLAayKNhMqVNmMdT/llFOMuK6uzojfe++9nD/vvhdujz+/9dZbc/7sli1bjNi+p9+tW7f0clNTk7EuV2nociIivQC8AOAnqnpSbS333RW7fBZFj0d0yktEuiDVyJ9R1Rczvcd9d6Vv377hJkh5saFTTpIa9vckgAZVfSTqfKg4bOiUz1gA0wBcKyJrnD8To06KClM2ffSvvvrKiFetMq8HDRkyxIjtZ8bd5aHOPfdcY53d/7enZNqxY4cRjx071ohPnDiRXrbHthfaR4/6vrlNVVcCkLxvpFjjEZ0oAdjQiRKADZ0oAcqmj75p0yYjtp/rtm/p2M+MX3HFFenl999/31i3fPlyI16xYoUR2/fZv/76ayP+/PPP08vu2nQAsG/fPuRi35M/duxYzvcTFaNsGjqVj+bm5pPmiS/GP/3TP/lPxhFUZZgf/ehHgWwHxeXA0wAAG2hJREFUADp18n9C/cQTT3j7LN+fRESxVzZHdHtoqR3bFi1aZMS1tbXpZXsmlr179xrxNddcY8R2/TP7UdKXXnopvfzcc8/lzMtW6KwwRMXgEZ0oAdjQiRKADZ0oAcqmj+5Xrj59VVWVEY8YMcKI3TOxAidfLZ0zZ47nPDp3Nnf58ePHPf8sUbF4RCdKADZ0ogRgQydKgMT00XOxh6HapZDsKZifeuopI7ZLTeXinr6JKCw8ohMlABs6UQKwoRMlAPvoAO644w4jtqdk2rBhgxHPnTvX87bt++b247VEYeARnSgB2NCJEoANnSgBEtlHt8ey2+Wbu3fvbsT2dE/bt2/3/FltbW0FZkcUvEQ2dCqttra2vLXyvJgxY0YA2aQsXbo0kO20tLQEsh0AuPLKK31vo6GhwdP7vMyPPlRElonIRhHZICL3OK/3F5ElItLo/N3PZ85EVCJe+uhtAH6mqvUAxgC4W0TqAcwCsFRVhwNY6sREFEN5T91VtQlAk7N8REQaAAwGMAnAOOdtcwEsB3BfSbIM2Nlnn23EZ511lhHb976XLVtmxCzJTOWmoD66iNQBuBjAKgA1zn8CALAXQE2Wn0nPm01E0fB8e01EeiE1R/ZPVPWwe52mSplmLGfqnjfbV6YUKRGpEpEPRWRR/ndT3Hg6ootIF6Qa+TOq+qLz8j4RqVXVJhGpBdBcqiSD1t7ebsT79+83YrvY/5tvvul523369DHiQ4cOFZhdbN0DoAFAddSJUOG8XHUXAE8CaFDVR1yrFgKY7ixPB7Ag+PQoDkRkCICbAXibFoRix8sRfSyAaQA+EpE1zms/B/AwgOdFZAaAnQBuL02KFAOPArgXQO9sb3Bfi+nWrVtIaZFXXq66rwSQrSzK+GDTobgRkVsANKvq+yIyLtv7VHU2gNkA0Lt3b04/EzOJHBnX2NhoxL/61a+M2J5tNR93uegK6pN3GAvgVhGZCKA7gGoRmaeqd0acFxWAD7VQTqp6v6oOUdU6AFMAvM5GXn7Y0IkSIJGn7lQcVV2O1AhIKjOJbOhbt24NdHuc+pjijqfuRAnAhk6UAGzoRAkgYfYvReQzpEbRDQSwP8/bo1BJeQ1T1UGlSCYf1+85l7jt67jlA3jLydPvOdSGnv5QkdVxfJqNeYUnbv+muOUDBJsTT92JEoANnSgBomrosyP63HyYV3ji9m+KWz5AgDlF0kcnonDx1J0oAUJt6CIyQUQ2i8hWEYm0PLSIzBGRZhFZ73ot0lr1SaihH6fvgJNPxn0etaBr9IXW0EWkCsDjAG4CUA9gqlMfPipPA5hgvRZ1rfqKrqEfw+8AkH2fR62jRl8gwjyijwawVVW3q2oLgGeRqg0fCVVdAeCA9fIkpGrUw/l7csg5NanqB87yEaR+0R019CPLK0Cx+g4AOfd5ZEpRoy/Mhj4YwC5XvBsR79AMPNWqD0MxNfTLQKy/A9Y+j1JHjb72fG/0ihfjsshVq77Uiq2hT8XLtc9DziNdoy/I7YbZ0PcAGOqKhzivxck+p0Y9oqpVn6uGfpR5BSSW34Es+zwqHTX6diDVtblWROb53WiYDf09AMNF5EwR6YpU/bGFIX6+F5HWqk9ADf3YfQdy7PNIlKxGn6qG9gfARABbAGwD8ECYn50hl/lITR7ZilRfcQaAAUhd1W4E8BqA/iHndAVSp+XrAKxx/kyMOq9K/Q7k2udR5+XkNg7AoiC2xZFxRAng69Q9boMfiCizoo/ozuCHLQCuR+rU9z0AU1V1Y3DpEVEQ/FSBTQ9+AAAR6Rj8kLWhiwj7CSFS1WxTaZVU165dtUePHr63E+SsN507B1Pw+NRTTw1kOwDQqZP/a+EHDhzAl19+mff37Odfn2nww+U+tkcVokePHrjyyit9b2fRouCmYh84cGAg27nrrrsC2Q4A9OzZ0/c2HnnE242Cktd1d8+ySUTR8NPQPQ1+UNcsmzx1J4qGn05C7AY/EFFmRTd0VW0D8GMAf0LqiZ/nVXVDUIlRfPA2avnz1UdX1cUAFgeUC8WQ6xny9G1UEVnI26jlJZGTLPp1+umnG/HIkSPTyyNGjDDW2bdQNmwwT3oaGszaArt37w4ixSAVfBuV4oePqVI+sX6GnLxhQ6dAiMhMEVktIqtbWlqiTocsPHXPoL7eLBl2553mU4L2YJCuXbuml99/36wX8MYbbxjxvn37jPjLL7804i5duhhxa2urh4xLquDbqH379uVt1JjhEZ3y4W3UCsAjOuWkqm0i0nEbtQrAHN5GLT9s6JQXb6OWv0Q29G7duhnxbbfdZsTf//73jfiiiy4yYrvfvGPHjvTy0aNHjXXdu3c3YrtPfuzYMSNubw+s8CdRGvvoRAnAhk6UAIk8dafSqqqqQr9+/qeHGzNmTADZpPzDP/xDINv56KOPAtkOACxZssT3Ng4f9laCPjEN3T1s9cc//rGx7sYbbzTi2tpaI962bZsRr1plTuSxc+fO9PLx48eNdfYQV3tbRGHgqTtRArChEyUAGzpRAlRsH/3cc8814r/7u79LL1988cXGOvux061btxrx//zP/xjxq6++asSffPJJ0XkShYFHdKIEYEMnSgA2dKIEqJg+ut3P/sEPfmDE7nvjvXr1MtbZfex//dd/NeKXXnqp6LzOP/98I/7qq69yfrY9RVZbW1vRn03UgUd0ogRgQydKADZ0ogSomD76VVddZcTuEswA8Bd/8RfpZfuZcPc9dgB4+eWXi87jvvvuM2K7z/38888bcQxqwlEC8IhOlABs6EQJULan7pdfbk7Ffv311xuxPczV7YEHHjBiP6fqAPC73/0uvXzTTTcZ6xobG43YfkzVXYaKqFR4RCdKADZ0ogTIe+ouInMA3AKgWVVHOq/1B/AcgDoAOwDcrqoHS5cmlZOWlpZAnui74IILAsgmZfPmzYFsZ+XKlYFsBwD++q//2vc2Nm3a5Ol9XvroTwN4DMDvXa/NArBUVR925sueBeC+DD8bmNNOO82IJ0yYYMT2NEqDBg0y4qeeeiq9/Oyzzxb02fatul/84hdZ1/ft29dYd8oppxjxiRMnCvpsoiDkPXVX1RUADlgvTwIw11meC2BywHkRUYCK7aPXqGqTs7wXQE1A+RBRCfi+vaaqKiJZZ88UkZkAZvr9HCIqXrENfZ+I1Kpqk4jUAmjO9kb3dLq5/kPIx74vbpdkHjJkiBHbFykWLFiQXrYf/bSnKn7ooYeMeMqUKUZsT7PUp0+f9HKPHj2Mda+//roRL1q0CERhK/bUfSGA6c7ydAALcryXypiIDBWRZSKyUUQ2iMg9UedEhcvb0EVkPoC3AZwnIrtFZAaAhwFcLyKNAK5zYqpMbQB+pqr1AMYAuFtE6vP8DMVM3lN3VZ2aZdX4gHOhGHIuujY5y0dEpAHAYAAbI02MChLbse7ufi9w8v3pwYMHG7H9uOeaNWuM2N3HP+ecc4x1drmnSy+91IgPHDDvLtbUmDcZOnf+ZjcuW7bMWGf30cuZiNQBuBjAqgzr0hdd7WmpKXocAkueiEgvAC8A+ImqnjSzn6rOVtVRqjrKvrhJ0WNDp7xEpAtSjfwZVX0x6nyocGzolJOICIAnATSo6iNR50PFiW0f3R4j3rVrVyO2x4zbz323t7cbsfved6dO5v9vdp+7udkcFnDkyBEj/vTTT4342LFj6eV33nnHWGdfKyhDYwFMA/CRiHT8Y36uqosjzIkKFNuGTvGgqisBSNR5kD88dSdKADZ0ogSI7am7fe96586dRrx9+3Yjdt/LBoDly5cb8dq1a9PLdp/8//7v/4x4y5YtRnzZZZcZsf0svHvc/cGDZv0NOyaKQmwbOpWvlpaWk/5jLob9n7kfQc1h52cePpt9AbkYPXv29PQ+nroTJUBsj+gtLS1GbNf8Onr0aM543759Ruy+RZbvaDNixAgj/s53vmPE/fv3N+L9+/enlytpyCtVDh7RiRKADZ0oAdjQiRIgtn10m7sfDACff/65Edt9ej/sx1btIbD2lc533303vWwPjyWKAx7RiRKADZ0oAdjQiRKgbProdqkoe8irH1VVVUacegT7G9dcc40R9+7d24jffvvtwHIhKgUe0YkSgA2dKAHY0IkSoGz66LagnkYCTp5y6Z57zMlI7MdUf/3rXxux+z46URzxiE6UAGzoRAnAhk6UAGXbR/dj9OjRRnz11VcbsT0F87p164z41VdfLU1iRCWSyIZOpVVXV4fZs2f73o49cMkPu5hIsR577LFAtgMAixYt8r2NTz75xNP7vEybnHF+bBHpLyJLRKTR+bufz5yJqES89NGzzY89C8BSVR0OYKkTE1EMeZkfPdv82JMAjHPeNhfAcgD3lSTLALindKqrqzPW2eWf+/UzT04WLzZnH3rttdeCTY6oxAq66m7Nj13j/CcAAHsB1GT5MSKKmOeGnmt+bFVVAJrl52aKyGoRWe0rU4qUiFSJyIci4v8KEoXO01X3LPNj7xORWlVtEpFaAM2ZflZVZwOY7Wwn438GYXCXaM5X9N4+VX/wwQdLklOZuQdAA4DqqBOhwnm56p5tfuyFAKY7y9MBLAg+PYoDERkC4GYAT0SdCxXHyxE94/zYAB4G8LyIzACwE8DtpUmRYuBRAPcC6J3vjRRPXq6655ofe3yw6VDciMgtAJpV9X0RGZfjfTMBzAROvotB0UvMyLjjx4+nl+2SzPZjpq+88ooR7927t3SJxd9YALeKyEQA3QFUi8g8Vb3T/Sb3tZjzzjsvsmsxlBkfaqGcVPV+VR2iqnUApgB43W7kFH9s6EQJkJhTd/JPVZcjNQKSykxiGvqhQ4fSy2vXrjXW2dMo55tWmajc8NSdKAHY0IkSgA2dKAEk9TxKSB8m8hlSo+gGAtif5+1RqKS8hqnqoFIkk4/r95xL3PZ13PIBvOXk6fccakNPf6jIalUdFfoH58G8whO3f1Pc8gGCzYmn7kQJwIZOlABRNXT/JUJLg3mFJ27/prjlAwSYUyR9dCIKF0/diRIg1IYuIhNEZLOIbBWRSMtDi8gcEWkWkfWu1yKtVZ+EGvpx+g44+WTc51ELukZfaA1dRKoAPA7gJgD1AKY69eGj8jSACdZrUdeqr+ga+jH8DgDZ93nUOmr0BSLMI/poAFtVdbuqtgB4Fqna8JFQ1RUADlgvT0KqRj2cvyeHnFOTqn7gLB9B6hfdUUM/srwCFKvvAJBzn0emFDX6wmzogwHscsW7EfEOzSA2teortIZ+rL8D1j6PUkeNvvagNsiLcVnkqlVfasXW0Kfi5drnIeeRrtEX5HbDbOh7AAx1xUOc1+Jkn1OjHrlq1ZdSrhr6UeYVkFh+B7Ls86h01OjbgVTX5loRmed3o2E29PcADBeRM0WkK1L1xxaG+PleRFqrPgE19GP3HcixzyNRshp9qhraHwATAWwBsA3AA2F+doZc5iM1eWQrUn3FGQAGIHVVuxHAawD6h5zTFUidlq8DsMb5MzHqvCr1O5Brn0edl5PbOACLgtgWR8YRJQAvxhElgK+GHrdRTkSUWdGn7s4opy0Arkeqj/segKmqujHHz7CfECJVzTaVVkn16tVLBwwY4Hs7TU1N+d/kUWtrayDb6d69eyDbAYB+/fyPZP7iiy9w7NixvL9nP+We06OcAEBEOkY5ZW3olAwDBgzA/fff73s7//zP/xxANin2NFzFOueccwLZDgBMnux/gOOTTz7p6X1+Tt09jXISkZkislpEVvv4LCLyoeQTOKhr8j2euhNFw88RPZajnIjoZH4aeuxGORFRZkU3dFVtA/BjAH9C6tG+51V1Q1CJUXzwNmr589VHV9XFABYHlAvFkKtYRPo2qogszHUbleInMbOpllJNTU3GZQDo0qWLEe/atcuIm5tj/yAab6NWAA6BpXxiXSyCvGFDp0C4x0scPXo06nTIwlN3D84++2wjvuiii4x4+PDh6WV7WGNbW5sRb9682YiXLVtmxPapfQx4uo3qHi8xbNgwjpeIGR7RKR/eRq0APKJTTqraJiIdt1GrAMzhbdTyw4ZOefE2avljQwfQq1cvI/7e975nxFOmTDHiSy65xIg7d/5mN37wwQfGuvXr1xux/fhmdXV1YckSFYF9dKIEYEMnSgCeulPgVBUtLS2+txNkNRd7hGKxrrzyykC2AwBvvfWW7214HbOQyIY+cuRII/7BD35gxDfeeKMR19XVGbHd737jjTfSy3Ylkx07dhjxkSNHjDhVVpyotHjqTpQAbOhECcCGTpQAiemjjxs3Lr38wx/+0Fh3xRVXGHGfPn2MeP78+Ub8m9/8xoi3bNlSdF49e/Ys+meJvOIRnSgB2NCJEoANnSgBKraPbj8z7h6vPnbs2Jw/e++99xrxU089FVxilh49euRc/+WXX5bssyk5eEQnSgA2dKIEYEMnSoCK6aMPGzbMiO1nys8///z0sj3e/Fe/+pUR//GPfyw6j9NPP92IzzjjDCOuqqoy4q+//tqI7bHx7KNTEHhEJ0oANnSiBKiYU/fLLrvMiMeMGWPE7lNge/J4P6fqAHDXXXell2+44QZjnf1c9oYNZl3F5cuXG/HBgwd95UKUCY/oRAnAhk6UAHlP3UVkDoBbADSr6kjntf4AngNQB2AHgNtVleecBADYt2/fSU/4FePBBx8MIJsUuzpvsR599NFAtgOcfAemGKNGjfL0Pi999KcBPAbg967XZgFYqqoPO/NlzwJwX4E5+mI/WnrLLbcYce/evY3YPfXR008/XdBn2eWgf/SjHxnxddddl16ur6831jU2Nhrxxx9/bMQHDhwoKBeiYuQ9dVfVFQDsb+MkAHOd5bkAJgecFxEFqNir7jWq2uQs7wVQk+2NIjITwMwiP4eIAuD79pqqqohknT3TPctmrvcRUekU29D3iUitqjaJSC2A5iCTysSeyuiCCy4w4tNOO82It23bZsQvvvhi1m136mT2YG666SYjtqdksh+Bra2tTS9/8cUXxrqVK1casT1Nsj3EtbW1NWueURCRoUhdn6kBoABmq6r/K20UqmJvry0EMN1Zng5gQTDpUAy1AfiZqtYDGAPgbhGpz/MzFDN5G7qIzAfwNoDzRGS3iMwA8DCA60WkEcB1TkwVSFWbVPUDZ/kIgAYAg6PNigqV99RdVadmWTU+4Fwo5kSkDsDFAFZFmwkVqmzGug8ebB5ETj31VCO2H+9cu3atEbe1taWXb775ZmPd+PHm/1l/+Zd/acR2SWa7X71169b08qZNm4x19n30vXv3Zs0rzkSkF4AXAPxEVQ9nWJ++u+KeRprigUNgKS8R6YJUI39GVTNe1VTV2ao6SlVH2Rc3KXr8jVBOkpoF8kkADar6SNT5UHHY0CmfsQCmAbhWRNY4fyZGnRQVJradqa5duxpx3759jdi+T25Pi2T3E++88870sj3H9eWXX27Edqkp+963/YCEO1f7Z3fu3GnE5dIn76CqKwFwbucyxyM6UQKwoRMlABs6UQLEto9ul0E+duyYEdv3p+0x4gMHDjRid+22Xbt2Gevse+6vvPKKEbvvkwPA8OHDs8ZfffWVsW7dunUgilpsGzqVr9ra2kCqw9j/ofrx7W9/O5DtvPTSS4FsBwDWr1/vextNTU353wSeuhMlQmyP6Papu31Ly759ZpdVtmcpdd+OO3HihLFu9+7dOXPp16+fEY8bN86I3Y/IvvHGG8a6o0eP5tw2URh4RCdKADZ0ogRgQydKgNj20W3t7e1GbPfJbfbtOHvIbCGmT59uxPZjre7rBwsWsNgOxQ+P6EQJwIZOlABs6EQJUDZ99DDZpaauuuqqnO9fsmRJKdMh8o1HdKIEYEMnSgA2dKIEYB8dwIUXXmjEEyZMMGJ7bPybb75pxPa0S0RxwyM6UQKwoRMlABs6UQIkso9uzyRSX29ODlpdXW3Ezc3mrNAbNmwoTWJEJZLIhk6l1draij179vjeztChQwPIJsW+4FqsRx99NJDtAMDHH3/sexuHD580DV5GXqZNHioiy0Rko4hsEJF7nNf7i8gSEWl0/u6Xb1tEFA0vffQ2AD9T1XoAYwDcLSL1AGYBWKqqwwEsdWIiiiEv86M3AWhylo+ISAOAwQAmARjnvG0ugOUA7itJlgE766yzjNiuNnrKKacYsT0l86pVnB6cyktBfXQRqQNwMYBVAGqc/wQAYC+Amiw/k543m4ii4fn2moj0QmqO7J+oqnEFQFUVgGb6Ofe82b4ypUiJSJWIfCgii6LOhQrn6YguIl2QauTPqOqLzsv7RKRWVZtEpBZAc/YtRC81zXfKqaeeaqyzy0599NFHRmw/hnro0KGAsysL9wBoAFCd740UP16uuguAJwE0qOojrlULAXQUU5sOgMXSKpSIDAFwM4Anos6FiuPliD4WwDQAH4nIGue1nwN4GMDzIjIDwE4At5cmRYqBRwHcC6B31IlQcbxcdV8JQLKsHp/ldaoQInILgGZVfV9ExuV4X/qia58+fULKjrxKzMi4rl27ppftIbD2dE/vvPOOER8/frx0icXfWAC3ishEAN0BVIvIPFW90/0mVZ0NYDYADB48OOOFWYoOH2qhnFT1flUdoqp1AKYAeN1u5BR/bOhECZCYU3fyT1WXIzUCkspMYhq6uxzU2rVrjXVHjhwJOx2iUPHUnSgB2NCJEoANnSgBJPU8SkgfJvIZUqPoBgLYH9oHe1dJeQ1T1UGlSCYf1+85l7jt67jlA3jLydPvOdSGnv5QkdVxfJqNeYUnbv+muOUDBJsTT92JEoANnSgBomrosyP63HyYV3ji9m+KWz5AgDlF0kcnonDx1J0oAUJt6CIyQUQ2i8hWEYm0PLSIzBGRZhFZ73ot0lr1SaihH6fvgJNPxn0etaBr9IXW0EWkCsDjAG4CUA9gqlMfPipPA5hgvRZ1rfqKrqEfw+8AkH2fR62jRl8gwjyijwawVVW3q2oLgGeRqg0fCVVdAeCA9fIkpGrUw/l7csg5NanqB87yEaR+0R019CPLK0Cx+g4AOfd5ZEpRoy/Mhj4YwC5XvBsR79AMPNWqD0MxNfTLQKy/A9Y+j1JHjb72oDbIi3FZ5KpVX2rF1tCn4uXa5yHnka7RF+R2w2zoewC4p8cc4rwWJ/ucGvWIqlZ9rhr6UeYVkFh+B7Ls86h01OjbgVTX5loRmed3o2E29PcADBeRM0WkK1L1xxaG+PleRFqrPgE19GP3HcixzyNRshp9qhraHwATAWwBsA3AA2F+doZc5iM1eWQrUn3FGQAGIHVVuxHAawD6h5zTFUidlq8DsMb5MzHqvCr1O5Brn0edl5PbOACLgtgWR8YRJQAvxhElABs6UQKwoRMlABs6UQKwoRMlABs6UQKwoRMlABs6UQL8PzVK7W8f4h85AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 288x2880 with 40 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n1,n2,n3,n4 = x.shape\n",
    "fig,axs = plt.subplots(nrows = n2, ncols = 2,figsize=(4,2*n2))\n",
    "for (i,axi) in enumerate(axs[:,0]):\n",
    "    axi.imshow(np.matrix(x[0][i].data.numpy()),cmap='gray')\n",
    "for (i,axi) in enumerate(axs[:,1]):\n",
    "    axi.imshow(np.matrix(model.conv1.weight.data.data[i].numpy()),cmap='gray')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 50, 20, 20])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = F.max_pool2d(x, 2, 2)\n",
    "x = F.relu(model.conv2(x))\n",
    "x.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x7200 with 100 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n1,n2,n3,n4 = x.shape\n",
    "fig,axs = plt.subplots(nrows = n2, ncols = 2,figsize=(4,2*n2))\n",
    "for (i,axi) in enumerate(axs[:,0]):\n",
    "    axi.imshow(np.matrix(x[0][i].data.numpy()),cmap='gray')\n",
    "for (i,axi) in enumerate(axs[:,1]):\n",
    "    axi.imshow(np.matrix(model.conv2.weight.data.data[i].numpy()[0]),cmap='gray')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = F.relu(model.conv1(b))\n",
    "x = F.max_pool2d(x, 2, 2)\n",
    "x = F.relu(model.conv2(x))\n",
    "x = F.max_pool2d(x, 2, 2)\n",
    "x = x.view(-1, 4*4*50)\n",
    "x = F.relu(model.fc1(x))\n",
    "x = model.fc2(x)\n",
    "y = F.log_softmax(x, dim=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[-1.1071, -9.1743, -3.3233, -1.2702,  2.9894,  1.0990, -2.7832,  0.8262,\n",
       "          0.9356, 11.7905]], grad_fn=<AddmmBackward>)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(x.data.numpy(),cmap='gray')\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2.5035176e-06, 7.8519441e-10, 2.7292884e-07, 2.1266437e-06,\n",
       "        1.5053307e-04, 2.2732060e-05, 4.6839153e-07, 1.7305088e-05,\n",
       "        1.9304320e-05, 9.9978447e-01]], dtype=float32)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(y.data.numpy(),cmap='gray')\n",
    "np.exp(y.data.numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
